hasil spss asumsi.docx

Upload: rajib-wahyu-nugroho-kartono

Post on 14-Apr-2018

226 views

Category:

Documents


0 download

TRANSCRIPT

  • 7/27/2019 hasil spss asumsi.docx

    1/117

    NPar TestsNotes

    Output Created 14-Sep-2013 10:25:05

    Comments

    Input Data C:\Users\dell\Documents\rajib.sav

    Active Dataset DataSet1

    Filter

    Weight

    Split File

    N of Rows in Working Data File 112

    Missing Value Handling Definition of Missing User-defined missing values are treated as

    missing.

    Cases Used Statistics for each test are based on all cases

    with valid data for the variable(s) used in that

    test.

    Syntax NPAR TESTS

    /K-S(NORMAL)=Keuangan Peralatan

    Pengalaman Kemampuan Mutu

    Keselamatan Konser Waktu Kualitas K_3

    Biaya Lingk

    /MISSING ANALYSIS.

    Resources Processor Timea 00:00:00.015

    Elapsed Time 00:00:00.016

    Number of Cases Allowed 52428

    a. Based on availability of workspace memory.

    [DataSet1] C:\Users\dell\Documents\rajib.savOne-Sample Kolmogorov-Smirnov Test

    N

    Normal Parameters Most Extreme DifferencesKolmogorov-Smirn

    ov Z

    Asymp. Sig.

    (2-tailed)Mean Std. Deviation Absolute Positive Negative

    Keuangan 112 14.2232 1.70167 .173 .166 -.173 1.833 .002

    Peralatan/Perlengkapan 112 14.1429 1.72870 .219 .219 -.144 2.317 .000

    Pengalaman Kerja 112 10.2143 1.33847 .327 .327 -.204 3.458 .000

    Sisa Kemampuan Biaya 112 3.5893 .49417 .386 .294 -.386 4.089 .000

  • 7/27/2019 hasil spss asumsi.docx

    2/117

    Manajemen Mutu 112 10.8750 1.34984 .244 .179 -.244 2.584 .000

    Keselamatan Kerja 112 17.3929 1.96985 .168 .168 -.132 1.781 .004

    Konservasi Lingkungan 112 5.8571 1.22185 .173 .142 -.173 1.835 .002

    Kinerja berdasarkan Waktu 112 21.7054 2.17537 .176 .141 -.176 1.859 .002

    Kinerja berdasarkan Kualitas 112 22.0982 1.84518 .173 .173 -.157 1.831 .002

    Kinerja berdasarkan K3 112 14.5536 1.64858 .148 .148 -.125 1.571 .014

    Kinerja berdasarkan Biaya 112 25.8929 2.04171 .178 .178 -.108 1.884 .002

    Kinerja berdasarkan Lingkungan 112 13.2679 1.75007 .221 .221 -.154 2.338 .000

    Curve FitNotes

    Output Created 14-Sep-2013 10:31:28

    Comments

    Input Data C:\Users\dell\Documents\rajib.sav

    Active Dataset DataSet1

    Filter

    Weight

    Split File

    N of Rows in Working Data File 112

    Missing Value Handling Definition of Missing User-defined missing values are treated as

    missing.

    Cases Used Cases with a missing value in any variable

    are not used in the analysis.

    Syntax CURVEFIT

    /VARIABLES=Waktu WITH Keuangan

    /CONSTANT

    /MODEL=LINEAR

    /PLOT NONE.

    Resources Processor Time 00:00:00.031

    Elapsed Time 00:00:00.016

    Use From First observation

    To Last observation

    Predict From First Observation following the use period

    To Last observation

    Time Series Settings (TSET) Amount of Output PRINT = DEFAULT

  • 7/27/2019 hasil spss asumsi.docx

    3/117

    Saving New Variables NEWVAR = NONE

    Maximum Number of Lags in

    Autocorrelation or Partial

    Autocorrelation Plots

    MXAUTO = 16

    Maximum Number of Lags Per

    Cross-Correlation PlotsMXCROSS = 7

    Maximum Number of New

    Variables Generated Per

    Procedure

    MXNEWVAR = 60

    Maximum Number of New Cases

    Per ProcedureMXPREDICT = 1000

    Treatment of User-Missing

    ValuesMISSING = EXCLUDE

    Confidence Interval Percentage

    ValueCIN = 95

    Tolerance for Entering Variables

    in Regression EquationsTOLER = .0001

    Maximum Iterative Parameter

    ChangeCNVERGE = .001

    Method of Calculating Std.

    Errors for AutocorrelationsACFSE = IND

    Length of Seasonal Period Unspecified

    Variable Whose Values Label

    Observations in PlotsUnspecified

    Equations Include CONSTANT

    [DataSet1] C:\Users\dell\Documents\rajib.savCase Processing Summary

    N

    Total Cases 112

    Excluded Casesa

    0

    Forecasted Cases 0

    Newly Created Cases 0

    a. Cases with a missing value in any

    variable are excluded from the analysis.

  • 7/27/2019 hasil spss asumsi.docx

    4/117

    Variable Processing Summary

    Variables

    Dependent Independent

    Kinerja

    berdasarkan

    Waktu Keuangan

    Number of Positive Values 112 112

    Number of Zeros 0 0

    Number of Negative Values 0 0

    Number of Missing Values User-Missing 0 0

    System-Missing 0 0

    Model Summary and Parameter Estimates

    Dependent Variable:Kinerja berdasarkan Waktu

    Equation

    Model Summary Parameter Estimates

    R Square F df1 df2 Sig. Constant b1

    Linear .009 .981 1 110 .324 23.415 -.120

    The independent variable is Keuangan.

    * Curve Estimation.TSET NEWVAR=NONE.CURVEFIT/VARIABLES=Kualitas WITH Keuangan/CONSTANT/MODEL=LINEAR

    /PLOT NONE.Curve Fit

    Notes

    Output Created 14-Sep-2013 10:31:50

    Comments

    Input Data C:\Users\dell\Documents\rajib.sav

    Active Dataset DataSet1

    Filter

    Weight

    Split File

    N of Rows in Working Data File 112

  • 7/27/2019 hasil spss asumsi.docx

    5/117

    Missing Value Handling Definition of Missing User-defined missing values are treated as

    missing.

    Cases Used Cases with a missing value in any variable

    are not used in the analysis.

    Syntax CURVEFIT

    /VARIABLES=Kualitas WITH Keuangan

    /CONSTANT

    /MODEL=LINEAR

    /PLOT NONE.

    Resources Processor Time 00:00:00.015

    Elapsed Time 00:00:00.015

    Use From First observation

    To Last observation

    Predict From First Observation following the use period

    To Last observation

    Time Series Settings (TSET) Amount of Output PRINT = DEFAULT

    Saving New Variables NEWVAR = NONE

    Maximum Number of Lags in

    Autocorrelation or Partial

    Autocorrelation Plots

    MXAUTO = 16

    Maximum Number of Lags Per

    Cross-Correlation PlotsMXCROSS = 7

    Maximum Number of New

    Variables Generated Per

    Procedure

    MXNEWVAR = 60

    Maximum Number of New Cases

    Per ProcedureMXPREDICT = 1000

    Treatment of User-Missing

    ValuesMISSING = EXCLUDE

    Confidence Interval Percentage

    ValueCIN = 95

    Tolerance for Entering Variables

    in Regression EquationsTOLER = .0001

    Maximum Iterative Parameter

    ChangeCNVERGE = .001

    Method of Calculating Std.

    Errors for AutocorrelationsACFSE = IND

    Length of Seasonal Period Unspecified

  • 7/27/2019 hasil spss asumsi.docx

    6/117

    Variable Whose Values Label

    Observations in PlotsUnspecified

    Equations Include CONSTANT

    [DataSet1] C:\Users\dell\Documents\rajib.savModel Description

    Model Name MOD_5

    Dependent Variable 1 Kinerja berdasarkan Kualitas

    Equation 1 Linear

    Independent Variable Keuangan

    Constant Included

    Variable Whose Values Label Observations in Plots Unspecified

    Case Processing Summary

    N

    Total Cases 112

    Excluded Casesa 0

    Forecasted Cases 0

    Newly Created Cases 0

    a. Cases with a missing value in any

    variable are excluded from the analysis.

    Variable Processing Summary

    Variables

    Dependent Independent

    Kinerja

    berdasarkan

    Kualitas Keuangan

    Number of Positive Values 112 112

    Number of Zeros 0 0

    Number of Negative Values 0 0

    Number of Missing Values User-Missing 0 0

    System-Missing 0 0

  • 7/27/2019 hasil spss asumsi.docx

    7/117

    Model Summary and Parameter Estimates

    Dependent Variable:Kinerja berdasarkan Kualitas

    Equation

    Model Summary Parameter Estimates

    R Square F df1 df2 Sig. Constant b1

    Linear .000 .005 1 110 .941 22.207 -.008

    The independent variable is Keuangan.

    * Curve Estimation.TSET NEWVAR=NONE.CURVEFIT/VARIABLES=K_3 WITH Keuangan/CONSTANT/MODEL=LINEAR

    /PLOT NONE.Curve Fit

    Notes

    Output Created 14-Sep-2013 10:32:27

    Comments

    Input Data C:\Users\dell\Documents\rajib.sav

    Active Dataset DataSet1

    Filter

    Weight

    Split File

    N of Rows in Working Data File 112

    Missing Value Handling Definition of Missing User-defined missing values are treated as

    missing.

    Cases Used Cases with a missing value in any variable

    are not used in the analysis.

    Syntax CURVEFIT

    /VARIABLES=K_3 WITH Keuangan

    /CONSTANT

    /MODEL=LINEAR

    /PLOT NONE.

    Resources Processor Time 00:00:00.031

    Elapsed Time 00:00:00.015

  • 7/27/2019 hasil spss asumsi.docx

    8/117

    Use From First observation

    To Last observation

    Predict From First Observation following the use period

    To Last observation

    Time Series Settings (TSET) Amount of Output PRINT = DEFAULT

    Saving New Variables NEWVAR = NONE

    Maximum Number of Lags in

    Autocorrelation or Partial

    Autocorrelation Plots

    MXAUTO = 16

    Maximum Number of Lags Per

    Cross-Correlation PlotsMXCROSS = 7

    Maximum Number of New

    Variables Generated Per

    Procedure

    MXNEWVAR = 60

    Maximum Number of New Cases

    Per ProcedureMXPREDICT = 1000

    Treatment of User-Missing

    ValuesMISSING = EXCLUDE

    Confidence Interval Percentage

    ValueCIN = 95

    Tolerance for Entering Variables

    in Regression EquationsTOLER = .0001

    Maximum Iterative Parameter

    ChangeCNVERGE = .001

    Method of Calculating Std.

    Errors for AutocorrelationsACFSE = IND

    Length of Seasonal Period Unspecified

    Variable Whose Values Label

    Observations in PlotsUnspecified

    Equations Include CONSTANT

    [DataSet1] C:\Users\dell\Documents\rajib.savModel Description

    Model Name MOD_6

    Dependent Variable 1 Kinerja berdasarkan K3

    Equation 1 Linear

    Independent Variable Keuangan

  • 7/27/2019 hasil spss asumsi.docx

    9/117

  • 7/27/2019 hasil spss asumsi.docx

    10/117

    /MODEL=LINEAR

    /PLOT NONE.Curve Fit

    Notes

    Output Created 14-Sep-2013 10:32:46

    Comments

    Input Data C:\Users\dell\Documents\rajib.sav

    Active Dataset DataSet1

    Filter

    Weight

    Split File

    N of Rows in Working Data File 112

    Missing Value Handling Definition of Missing User-defined missing values are treated as

    missing.

    Cases Used Cases with a missing value in any variable

    are not used in the analysis.

    Syntax CURVEFIT

    /VARIABLES=Biaya WITH Keuangan

    /CONSTANT

    /MODEL=LINEAR

    /PLOT NONE.

    Resources Processor Time 00:00:00.031

    Elapsed Time 00:00:00.015

    Use From First observation

    To Last observation

    Predict From First Observation following the use period

    To Last observation

    Time Series Settings (TSET) Amount of Output PRINT = DEFAULT

    Saving New Variables NEWVAR = NONE

    Maximum Number of Lags in

    Autocorrelation or Partial

    Autocorrelation Plots

    MXAUTO = 16

    Maximum Number of Lags Per

    Cross-Correlation PlotsMXCROSS = 7

  • 7/27/2019 hasil spss asumsi.docx

    11/117

    Maximum Number of New

    Variables Generated Per

    Procedure

    MXNEWVAR = 60

    Maximum Number of New Cases

    Per ProcedureMXPREDICT = 1000

    Treatment of User-Missing

    ValuesMISSING = EXCLUDE

    Confidence Interval Percentage

    ValueCIN = 95

    Tolerance for Entering Variables

    in Regression EquationsTOLER = .0001

    Maximum Iterative Parameter

    ChangeCNVERGE = .001

    Method of Calculating Std.

    Errors for AutocorrelationsACFSE = IND

    Length of Seasonal Period Unspecified

    Variable Whose Values Label

    Observations in PlotsUnspecified

    Equations Include CONSTANT

    [DataSet1] C:\Users\dell\Documents\rajib.savModel Description

    Model Name MOD_7

    Dependent Variable 1 Kinerja berdasarkan Biaya

    Equation 1 Linear

    Independent Variable Keuangan

    Constant Included

    Variable Whose Values Label Observations in Plots Unspecified

    Case Processing Summary

    N

    Total Cases 112

    Excluded Casesa

    0

    Forecasted Cases 0

    Newly Created Cases 0

  • 7/27/2019 hasil spss asumsi.docx

    12/117

    Case Processing Summary

    N

    Total Cases 112

    Excluded Casesa

    0

    Forecasted Cases 0

    Newly Created Cases 0

    a. Cases with a missing value in any

    variable are excluded from the analysis.

    Variable Processing Summary

    Variables

    Dependent Independent

    Kinerja

    berdasarkan Biaya Keuangan

    Number of Positive Values 112 112

    Number of Zeros 0 0

    Number of Negative Values 0 0

    Number of Missing Values User-Missing 0 0

    System-Missing 0 0

    Model Summary and Parameter Estimates

    Dependent Variable:Kinerja berdasarkan Biaya

    Equation

    Model Summary Parameter Estimates

    R Square F df1 df2 Sig. Constant b1

    Linear .038 4.362 1 110 .039 29.226 -.234

    The independent variable is Keuangan.

    * Curve Estimation.TSET NEWVAR=NONE.CURVEFIT/VARIABLES=Lingk WITH Keuangan/CONSTANT/MODEL=LINEAR

    /PLOT NONE.Curve Fit

  • 7/27/2019 hasil spss asumsi.docx

    13/117

    Notes

    Output Created 14-Sep-2013 10:33:04

    Comments

    Input Data C:\Users\dell\Documents\rajib.sav

    Active Dataset DataSet1

    Filter

    Weight

    Split File

    N of Rows in Working Data File 112

    Missing Value Handling Definition of Missing User-defined missing values are treated as

    missing.

    Cases Used Cases with a missing value in any variable

    are not used in the analysis.

    Syntax CURVEFIT

    /VARIABLES=Lingk WITH Keuangan

    /CONSTANT

    /MODEL=LINEAR

    /PLOT NONE.

    Resources Processor Time 00:00:00.031

    Elapsed Time 00:00:00.015

    Use From First observation

    To Last observation

    Predict From First Observation following the use period

    To Last observation

    Time Series Settings (TSET) Amount of Output PRINT = DEFAULT

    Saving New Variables NEWVAR = NONE

    Maximum Number of Lags in

    Autocorrelation or Partial

    Autocorrelation Plots

    MXAUTO = 16

    Maximum Number of Lags Per

    Cross-Correlation PlotsMXCROSS = 7

    Maximum Number of New

    Variables Generated Per

    Procedure

    MXNEWVAR = 60

    Maximum Number of New Cases

    Per ProcedureMXPREDICT = 1000

    Treatment of User-Missing

    ValuesMISSING = EXCLUDE

  • 7/27/2019 hasil spss asumsi.docx

    14/117

    Confidence Interval Percentage

    ValueCIN = 95

    Tolerance for Entering Variables

    in Regression EquationsTOLER = .0001

    Maximum Iterative Parameter

    ChangeCNVERGE = .001

    Method of Calculating Std.

    Errors for AutocorrelationsACFSE = IND

    Length of Seasonal Period Unspecified

    Variable Whose Values Label

    Observations in PlotsUnspecified

    Equations Include CONSTANT

    [DataSet1] C:\Users\dell\Documents\rajib.savModel Description

    Model Name MOD_8

    Dependent Variable 1 Kinerja berdasarkan Lingkungan

    Equation 1 Linear

    Independent Variable Keuangan

    Constant Included

    Variable Whose Values Label Observations in Plots Unspecified

    Case Processing Summary

    N

    Total Cases 112

    Excluded Casesa

    0

    Forecasted Cases 0

    Newly Created Cases 0

    a. Cases with a missing value in any

    variable are excluded from the analysis.

    Variable Processing Summary

    Variables

    Dependent Independent

  • 7/27/2019 hasil spss asumsi.docx

    15/117

  • 7/27/2019 hasil spss asumsi.docx

    16/117

  • 7/27/2019 hasil spss asumsi.docx

    17/117

    [DataSet1] C:\Users\dell\Documents\rajib.sav

    Model Description

    Model Name MOD_9

    Dependent Variable 1 Kinerja berdasarkan Waktu

    Equation 1 Linear

    Independent Variable Personil

    Constant Included

    Variable Whose Values Label Observations in Plots Unspecified

    Case Processing Summary

    N

    Total Cases 112

    Excluded Casesa

    0

    Forecasted Cases 0

    Newly Created Cases 0

    a. Cases with a missing value in any

    variable are excluded from the analysis.

    Variable Processing Summary

    Variables

    Dependent Independent

    Kinerja

    berdasarkan

    Waktu Personil

    Number of Positive Values 112 112

    Number of Zeros 0 0

    Number of Negative Values 0 0

    Number of Missing Values User-Missing 0 0

    System-Missing 0 0

    Model Summary and Parameter Estimates

  • 7/27/2019 hasil spss asumsi.docx

    18/117

    Dependent Variable:Kinerja berdasarkan Waktu

    Equation

    Model Summary Parameter Estimates

    R Square F df1 df2 Sig. Constant b1

    Linear .002 .241 1 110 .624 22.666 -.045

    The independent variable is Personil.

    * Curve Estimation.TSET NEWVAR=NONE.CURVEFIT/VARIABLES=Kualitas WITH Personil/CONSTANT/MODEL=LINEAR

    /PLOT NONE.Curve Fit

    Notes

    Output Created 14-Sep-2013 10:34:03

    Comments

    Input Data C:\Users\dell\Documents\rajib.sav

    Active Dataset DataSet1

    Filter

    Weight

    Split File

    N of Rows in Working Data File 112

    Missing Value Handling Definition of Missing User-defined missing values are treated as

    missing.

    Cases Used Cases with a missing value in any variable

    are not used in the analysis.

    Syntax CURVEFIT

    /VARIABLES=Kualitas WITH Personil

    /CONSTANT

    /MODEL=LINEAR

    /PLOT NONE.

    Resources Processor Time 00:00:00.016

    Elapsed Time 00:00:00.014

    Use From First observation

    To Last observation

    Predict From First Observation following the use period

  • 7/27/2019 hasil spss asumsi.docx

    19/117

    To Last observation

    Time Series Settings (TSET) Amount of Output PRINT = DEFAULT

    Saving New Variables NEWVAR = NONE

    Maximum Number of Lags in

    Autocorrelation or Partial

    Autocorrelation Plots

    MXAUTO = 16

    Maximum Number of Lags Per

    Cross-Correlation PlotsMXCROSS = 7

    Maximum Number of New

    Variables Generated Per

    Procedure

    MXNEWVAR = 60

    Maximum Number of New Cases

    Per ProcedureMXPREDICT = 1000

    Treatment of User-Missing

    ValuesMISSING = EXCLUDE

    Confidence Interval Percentage

    ValueCIN = 95

    Tolerance for Entering Variables

    in Regression EquationsTOLER = .0001

    Maximum Iterative Parameter

    ChangeCNVERGE = .001

    Method of Calculating Std.

    Errors for AutocorrelationsACFSE = IND

    Length of Seasonal Period Unspecified

    Variable Whose Values Label

    Observations in PlotsUnspecified

    Equations Include CONSTANT

    [DataSet1] C:\Users\dell\Documents\rajib.savModel Description

    Model Name MOD_10

    Dependent Variable 1 Kinerja berdasarkan Kualitas

    Equation 1 Linear

    Independent Variable Personil

    Constant Included

    Variable Whose Values Label Observations in Plots Unspecified

  • 7/27/2019 hasil spss asumsi.docx

    20/117

    Case Processing Summary

    N

    Total Cases 112

    Excluded Casesa

    0

    Forecasted Cases 0

    Newly Created Cases 0

    a. Cases with a missing value in any

    variable are excluded from the analysis.

    Variable Processing Summary

    Variables

    Dependent Independent

    Kinerja

    berdasarkan

    Kualitas Personil

    Number of Positive Values 112 112

    Number of Zeros 0 0

    Number of Negative Values 0 0

    Number of Missing Values User-Missing 0 0

    System-Missing 0 0

    Model Summary and Parameter Estimates

    Dependent Variable:Kinerja berdasarkan Kualitas

    Equation

    Model Summary Parameter Estimates

    R Square F df1 df2 Sig. Constant b1

    Linear .031 3.483 1 110 .065 25.148 -.143

    The independent variable is Personil.

    * Curve Estimation.TSET NEWVAR=NONE.CURVEFIT/VARIABLES=K_3 WITH Personil/CONSTANT/MODEL=LINEAR

    /PLOT NONE.

  • 7/27/2019 hasil spss asumsi.docx

    21/117

  • 7/27/2019 hasil spss asumsi.docx

    22/117

    Treatment of User-Missing

    ValuesMISSING = EXCLUDE

    Confidence Interval Percentage

    ValueCIN = 95

    Tolerance for Entering Variables

    in Regression EquationsTOLER = .0001

    Maximum Iterative Parameter

    ChangeCNVERGE = .001

    Method of Calculating Std.

    Errors for Autocorrelations ACFSE = IND

    Length of Seasonal Period Unspecified

    Variable Whose Values Label

    Observations in PlotsUnspecified

    Equations Include CONSTANT

    [DataSet1] C:\Users\dell\Documents\rajib.savModel Description

    Model Name MOD_11

    Dependent Variable 1 Kinerja berdasarkan K3

    Equation 1 Linear

    Independent Variable Personil

    Constant Included

    Variable Whose Values Label Observations in Plots Unspecified

    Case Processing Summary

    N

    Total Cases 112

    Excluded Casesa

    0

    Forecasted Cases 0

    Newly Created Cases 0

    a. Cases with a missing value in any

    variable are excluded from the analysis.

    Variable Processing Summary

  • 7/27/2019 hasil spss asumsi.docx

    23/117

    VariablesDependent Independent

    Kinerja

    berdasarkan K3 Personil

    Number of Positive Values 112 112

    Number of Zeros 0 0

    Number of Negative Values 0 0

    Number of Missing Values User-Missing 0 0

    System-Missing 0 0

    Model Summary and Parameter Estimates

    Dependent Variable:Kinerja berdasarkan K3

    Equation

    Model Summary Parameter Estimates

    R Square F df1 df2 Sig. Constant b1

    Linear .004 .476 1 110 .492 15.574 -.048

    The independent variable is Personil.

    * Curve Estimation.TSET NEWVAR=NONE.CURVEFIT/VARIABLES=Biaya WITH Personil/CONSTANT/MODEL=LINEAR

    /PLOT NONE.Curve Fit

    Notes

    Output Created 14-Sep-2013 10:34:49

    Comments

    Input Data C:\Users\dell\Documents\rajib.sav

    Active Dataset DataSet1

    Filter

    Weight

    Split File

    N of Rows in Working Data File 112

    Missing Value Handling Definition of Missing User-defined missing values are treated as

    missing.

  • 7/27/2019 hasil spss asumsi.docx

    24/117

    Cases Used Cases with a missing value in any variable

    are not used in the analysis.

    Syntax CURVEFIT

    /VARIABLES=Biaya WITH Personil

    /CONSTANT

    /MODEL=LINEAR

    /PLOT NONE.

    Resources Processor Time 00:00:00.031

    Elapsed Time 00:00:00.016

    Use From First observation

    To Last observation

    Predict From First Observation following the use period

    To Last observation

    Time Series Settings (TSET) Amount of Output PRINT = DEFAULT

    Saving New Variables NEWVAR = NONE

    Maximum Number of Lags in

    Autocorrelation or Partial

    Autocorrelation Plots

    MXAUTO = 16

    Maximum Number of Lags Per

    Cross-Correlation PlotsMXCROSS = 7

    Maximum Number of New

    Variables Generated Per

    Procedure

    MXNEWVAR = 60

    Maximum Number of New Cases

    Per ProcedureMXPREDICT = 1000

    Treatment of User-Missing

    ValuesMISSING = EXCLUDE

    Confidence Interval Percentage

    ValueCIN = 95

    Tolerance for Entering Variables

    in Regression EquationsTOLER = .0001

    Maximum Iterative Parameter

    ChangeCNVERGE = .001

    Method of Calculating Std.

    Errors for AutocorrelationsACFSE = IND

    Length of Seasonal Period Unspecified

    Variable Whose Values Label

    Observations in PlotsUnspecified

    Equations Include CONSTANT

  • 7/27/2019 hasil spss asumsi.docx

    25/117

    [DataSet1] C:\Users\dell\Documents\rajib.sav

    Model Description

    Model Name MOD_12

    Dependent Variable 1 Kinerja berdasarkan Biaya

    Equation 1 Linear

    Independent Variable Personil

    Constant Included

    Variable Whose Values Label Observations in Plots Unspecified

    Case Processing Summary

    N

    Total Cases 112

    Excluded Casesa

    0

    Forecasted Cases 0

    Newly Created Cases 0

    a. Cases with a missing value in any

    variable are excluded from the analysis.

    Variable Processing Summary

    Variables

    Dependent Independent

    Kinerja

    berdasarkan Biaya Personil

    Number of Positive Values 112 112

    Number of Zeros 0 0

    Number of Negative Values 0 0

    Number of Missing Values User-Missing 0 0

    System-Missing 0 0

    Model Summary and Parameter Estimates

    Dependent Variable:Kinerja berdasarkan Biaya

    M d l S P t E ti t

  • 7/27/2019 hasil spss asumsi.docx

    26/117

    Equation

    Model Summary Parameter Estimates

    R Square F df1 df2 Sig. Constant b1

    Linear .054 6.305 1 110 .013 30.378 -.211

    The independent variable is Personil.

    * Curve Estimation.TSET NEWVAR=NONE.CURVEFIT/VARIABLES=Lingk WITH Personil/CONSTANT

    /MODEL=LINEAR

    /PLOT NONE.Curve Fit

    Notes

    Output Created 14-Sep-2013 10:35:07

    Comments

    Input Data C:\Users\dell\Documents\rajib.sav

    Active Dataset DataSet1

    Filter

    Weight

    Split File

    N of Rows in Working Data File 112

    Missing Value Handling Definition of Missing User-defined missing values are treated as

    missing.

    Cases Used Cases with a missing value in any variable

    are not used in the analysis.

    Syntax CURVEFIT

    /VARIABLES=Lingk WITH Personil

    /CONSTANT

    /MODEL=LINEAR

    /PLOT NONE.

    Resources Processor Time 00:00:00.016

    Elapsed Time 00:00:00.016

    Use From First observation

    To Last observation

    Predict From First Observation following the use period

    To Last observation

    Time Series Settings (TSET) Amount of Output PRINT = DEFAULT

  • 7/27/2019 hasil spss asumsi.docx

    27/117

    Time Series Settings (TSET) Amount of Output PRINT DEFAULT

    Saving New Variables NEWVAR = NONE

    Maximum Number of Lags in

    Autocorrelation or Partial

    Autocorrelation Plots

    MXAUTO = 16

    Maximum Number of Lags Per

    Cross-Correlation PlotsMXCROSS = 7

    Maximum Number of New

    Variables Generated Per

    Procedure

    MXNEWVAR = 60

    Maximum Number of New Cases

    Per ProcedureMXPREDICT = 1000

    Treatment of User-Missing

    ValuesMISSING = EXCLUDE

    Confidence Interval Percentage

    ValueCIN = 95

    Tolerance for Entering Variables

    in Regression EquationsTOLER = .0001

    Maximum Iterative Parameter

    ChangeCNVERGE = .001

    Method of Calculating Std.

    Errors for AutocorrelationsACFSE = IND

    Length of Seasonal Period Unspecified

    Variable Whose Values Label

    Observations in PlotsUnspecified

    Equations Include CONSTANT

    [DataSet1] C:\Users\dell\Documents\rajib.sav

    Model Description

    Model Name MOD_13

    Dependent Variable 1 Kinerja berdasarkan Lingkungan

    Equation 1 Linear

    Independent Variable Personil

    Constant Included

    Variable Whose Values Label Observations in Plots Unspecified

    Case Processing Summary

  • 7/27/2019 hasil spss asumsi.docx

    28/117

    g y

    N

    Total Cases 112

    Excluded Casesa

    0

    Forecasted Cases 0

    Newly Created Cases 0

    a. Cases with a missing value in any

    variable are excluded from the analysis.

    Variable Processing Summary

    Variables

    Dependent Independent

    Kinerja

    berdasarkan

    Lingkungan Personil

    Number of Positive Values 112 112

    Number of Zeros 0 0

    Number of Negative Values 0 0

    Number of Missing Values User-Missing 0 0

    System-Missing 0 0

    Model Summary and Parameter Estimates

    Dependent Variable:Kinerja berdasarkan Lingkungan

    Equation

    Model Summary Parameter Estimates

    R Square F df1 df2 Sig. Constant b1

    Linear .012 1.326 1 110 .252 15.070 -.085

    The independent variable is Personil.

    * Curve Estimation.TSET NEWVAR=NONE.CURVEFIT/VARIABLES=Waktu WITH Peralatan/CONSTANT/MODEL=LINEAR

    /PLOT NONE.Curve Fit

  • 7/27/2019 hasil spss asumsi.docx

    29/117

    Notes

    Output Created 14-Sep-2013 10:35:44

    Comments

    Input Data C:\Users\dell\Documents\rajib.sav

    Active Dataset DataSet1

    Filter

    Weight

    Split File

    N of Rows in Working Data File 112

    Missing Value Handling Definition of Missing User-defined missing values are treated as

    missing.

    Cases Used Cases with a missing value in any variable

    are not used in the analysis.

    Syntax CURVEFIT

    /VARIABLES=Waktu WITH Peralatan

    /CONSTANT

    /MODEL=LINEAR

    /PLOT NONE.

    Resources Processor Time 00:00:00.032

    Elapsed Time 00:00:00.018

    Use From First observation

    To Last observation

    Predict From First Observation following the use period

    To Last observation

    Time Series Settings (TSET) Amount of Output PRINT = DEFAULT

    Saving New Variables NEWVAR = NONE

    Maximum Number of Lags in

    Autocorrelation or Partial

    Autocorrelation Plots

    MXAUTO = 16

    Maximum Number of Lags Per

    Cross-Correlation PlotsMXCROSS = 7

    Maximum Number of New

    Variables Generated Per

    Procedure

    MXNEWVAR = 60

    Maximum Number of New Cases

    Per ProcedureMXPREDICT = 1000

    Treatment of User-MissingMISSING = EXCLUDE

  • 7/27/2019 hasil spss asumsi.docx

    30/117

    ValuesMISSING = EXCLUDE

    Confidence Interval Percentage

    ValueCIN = 95

    Tolerance for Entering Variables

    in Regression EquationsTOLER = .0001

    Maximum Iterative Parameter

    ChangeCNVERGE = .001

    Method of Calculating Std.

    Errors for Autocorrelations

    ACFSE = IND

    Length of Seasonal Period Unspecified

    Variable Whose Values Label

    Observations in PlotsUnspecified

    Equations Include CONSTANT

    [DataSet1] C:\Users\dell\Documents\rajib.savModel Description

    Model Name MOD_14

    Dependent Variable 1 Kinerja berdasarkan Waktu

    Equation 1 Linear

    Independent Variable Peralatan/Perlengkapan

    Constant Included

    Variable Whose Values Label Observations in Plots Unspecified

    Case Processing Summary

    N

    Total Cases 112

    Excluded Casesa

    0

    Forecasted Cases 0

    Newly Created Cases 0

    a. Cases with a missing value in any

    variable are excluded from the analysis.

    Variable Processing Summary

    Variables

  • 7/27/2019 hasil spss asumsi.docx

    31/117

    Dependent Independent

    Kinerja

    berdasarkan

    Waktu

    Peralatan/Perlengk

    apan

    Number of Positive Values 112 112

    Number of Zeros 0 0

    Number of Negative Values 0 0

    Number of Missing Values User-Missing 0 0

    System-Missing 0 0

    Model Summary and Parameter Estimates

    Dependent Variable:Kinerja berdasarkan Waktu

    Equation

    Model Summary Parameter Estimates

    R Square F df1 df2 Sig. Constant b1

    Linear .006 .704 1 110 .403 23.125 -.100

    The independent variable is Peralatan/Perlengkapan.

    * Curve Estimation.TSET NEWVAR=NONE.CURVEFIT/VARIABLES=Kualitas WITH Peralatan/CONSTANT/MODEL=LINEAR

    /PLOT NONE.Curve Fit

    Notes

    Output Created 14-Sep-2013 10:36:20

    Comments

    Input Data C:\Users\dell\Documents\rajib.sav

    Active Dataset DataSet1

    Filter

    Weight

    Split File

    N of Rows in Working Data File 112

  • 7/27/2019 hasil spss asumsi.docx

    32/117

    Variable Whose Values Label

    Ob ti i Pl tUnspecified

  • 7/27/2019 hasil spss asumsi.docx

    33/117

    Observations in Plots

    Equations Include CONSTANT

    [DataSet1] C:\Users\dell\Documents\rajib.savModel Description

    Model Name MOD_15

    Dependent Variable 1 Kinerja berdasarkan Kualitas

    Equation 1 Linear

    Independent Variable Peralatan/Perlengkapan

    Constant Included

    Variable Whose Values Label Observations in Plots Unspecified

    Case Processing Summary

    N

    Total Cases 112

    Excluded Casesa 0

    Forecasted Cases 0

    Newly Created Cases 0

    a. Cases with a missing value in any

    variable are excluded from the analysis.

    Variable Processing Summary

    Variables

    Dependent Independent

    Kinerja

    berdasarkan

    Kualitas

    Peralatan/Perlengk

    apan

    Number of Positive Values 112 112

    Number of Zeros 0 0

    Number of Negative Values 0 0

    Number of Missing Values User-Missing 0 0

    System-Missing 0 0

  • 7/27/2019 hasil spss asumsi.docx

    34/117

    Model Summary and Parameter Estimates

    Dependent Variable:Kinerja berdasarkan Kualitas

    Equation

    Model Summary Parameter Estimates

    R Square F df1 df2 Sig. Constant b1

    Linear .001 .136 1 110 .713 21.568 .037

    The independent variable is Peralatan/Perlengkapan.

    * Curve Estimation.TSET NEWVAR=NONE.CURVEFIT/VARIABLES=K_3 WITH Peralatan/CONSTANT/MODEL=LINEAR

    /PLOT NONE.Curve Fit

    Notes

    Output Created 14-Sep-2013 10:36:36

    Comments

    Input Data C:\Users\dell\Documents\rajib.sav

    Active Dataset DataSet1

    Filter

    Weight

    Split File

    N of Rows in Working Data File 112

    Missing Value Handling Definition of Missing User-defined missing values are treated as

    missing.

    Cases Used Cases with a missing value in any variable

    are not used in the analysis.

    Syntax CURVEFIT

    /VARIABLES=K_3 WITH Peralatan

    /CONSTANT

    /MODEL=LINEAR

    /PLOT NONE.

    Resources Processor Time 00:00:00.031

    Elapsed Time 00:00:00.015

    Use From First observation

    To Last observation

  • 7/27/2019 hasil spss asumsi.docx

    35/117

    To Last observation

    Predict From First Observation following the use period

    To Last observation

    Time Series Settings (TSET) Amount of Output PRINT = DEFAULT

    Saving New Variables NEWVAR = NONE

    Maximum Number of Lags in

    Autocorrelation or Partial

    Autocorrelation Plots

    MXAUTO = 16

    Maximum Number of Lags Per

    Cross-Correlation PlotsMXCROSS = 7

    Maximum Number of New

    Variables Generated Per

    Procedure

    MXNEWVAR = 60

    Maximum Number of New Cases

    Per ProcedureMXPREDICT = 1000

    Treatment of User-Missing

    ValuesMISSING = EXCLUDE

    Confidence Interval Percentage

    ValueCIN = 95

    Tolerance for Entering Variables

    in Regression EquationsTOLER = .0001

    Maximum Iterative Parameter

    ChangeCNVERGE = .001

    Method of Calculating Std.

    Errors for AutocorrelationsACFSE = IND

    Length of Seasonal Period Unspecified

    Variable Whose Values Label

    Observations in PlotsUnspecified

    Equations Include CONSTANT

    [DataSet1] C:\Users\dell\Documents\rajib.savModel Description

    Model Name MOD_16

    Dependent Variable 1 Kinerja berdasarkan K3

    Equation 1 Linear

    Independent Variable Peralatan/Perlengkapan

  • 7/27/2019 hasil spss asumsi.docx

    36/117

  • 7/27/2019 hasil spss asumsi.docx

    37/117

    Maximum Number of New

    Variables Generated Per MXNEWVAR = 60

  • 7/27/2019 hasil spss asumsi.docx

    38/117

    Procedure

    Maximum Number of New Cases

    Per ProcedureMXPREDICT = 1000

    Treatment of User-Missing

    ValuesMISSING = EXCLUDE

    Confidence Interval Percentage

    ValueCIN = 95

    Tolerance for Entering Variablesin Regression Equations

    TOLER = .0001

    Maximum Iterative Parameter

    ChangeCNVERGE = .001

    Method of Calculating Std.

    Errors for AutocorrelationsACFSE = IND

    Length of Seasonal Period Unspecified

    Variable Whose Values Label

    Observations in PlotsUnspecified

    Equations Include CONSTANT

    [DataSet1] C:\Users\dell\Documents\rajib.savModel Description

    Model Name MOD_17

    Dependent Variable 1 Kinerja berdasarkan Biaya

    Equation 1 Linear

    Independent Variable Peralatan/Perlengkapan

    Constant Included

    Variable Whose Values Label Observations in Plots Unspecified

    Case Processing Summary

    N

    Total Cases 112

    Excluded Casesa

    0

    Forecasted Cases 0

    Newly Created Cases 0

    Case Processing Summary

    N

  • 7/27/2019 hasil spss asumsi.docx

    39/117

    Total Cases 112

    Excluded Casesa

    0

    Forecasted Cases 0

    Newly Created Cases 0

    a. Cases with a missing value in any

    variable are excluded from the analysis.

    Variable Processing Summary

    Variables

    Dependent Independent

    Kinerja

    berdasarkan Biaya

    Peralatan/Perlengk

    apan

    Number of Positive Values 112 112

    Number of Zeros 0 0

    Number of Negative Values 0 0

    Number of Missing Values User-Missing 0 0

    System-Missing 0 0

    Model Summary and Parameter Estimates

    Dependent Variable:Kinerja berdasarkan Biaya

    Equation

    Model Summary Parameter Estimates

    R Square F df1 df2 Sig. Constant b1

    Linear .106 12.981 1 110 .000 31.320 -.384

    The independent variable is Peralatan/Perlengkapan.

    * Curve Estimation.TSET NEWVAR=NONE.CURVEFIT/VARIABLES=Lingk WITH Peralatan/CONSTANT/MODEL=LINEAR

    /PLOT NONE.Curve Fit

    Notes

    Output Created 14-Sep-2013 10:37:12

  • 7/27/2019 hasil spss asumsi.docx

    40/117

    Comments

    Input Data C:\Users\dell\Documents\rajib.sav

    Active Dataset DataSet1

    Filter

    Weight

    Split File

    N of Rows in Working Data File 112

    Missing Value Handling Definition of Missing User-defined missing values are treated as

    missing.

    Cases Used Cases with a missing value in any variable

    are not used in the analysis.

    Syntax CURVEFIT

    /VARIABLES=Lingk WITH Peralatan

    /CONSTANT

    /MODEL=LINEAR

    /PLOT NONE.

    Resources Processor Time 00:00:00.016

    Elapsed Time 00:00:00.016

    Use From First observation

    To Last observation

    Predict From First Observation following the use period

    To Last observation

    Time Series Settings (TSET) Amount of Output PRINT = DEFAULT

    Saving New Variables NEWVAR = NONE

    Maximum Number of Lags in

    Autocorrelation or Partial

    Autocorrelation Plots

    MXAUTO = 16

    Maximum Number of Lags Per

    Cross-Correlation PlotsMXCROSS = 7

    Maximum Number of New

    Variables Generated Per

    Procedure

    MXNEWVAR = 60

    Maximum Number of New Cases

    Per ProcedureMXPREDICT = 1000

    Treatment of User-Missing

    ValuesMISSING = EXCLUDE

    Confidence Interval Percentage

    ValueCIN = 95

  • 7/27/2019 hasil spss asumsi.docx

    41/117

    Tolerance for Entering Variables

    in Regression EquationsTOLER = .0001

    Maximum Iterative Parameter

    ChangeCNVERGE = .001

    Method of Calculating Std.

    Errors for AutocorrelationsACFSE = IND

    Length of Seasonal Period Unspecified

    Variable Whose Values Label

    Observations in PlotsUnspecified

    Equations Include CONSTANT

    [DataSet1] C:\Users\dell\Documents\rajib.savModel Description

    Model Name MOD_18

    Dependent Variable 1 Kinerja berdasarkan Lingkungan

    Equation 1 Linear

    Independent Variable Peralatan/Perlengkapan

    Constant Included

    Variable Whose Values Label Observations in Plots Unspecified

    Case Processing Summary

    N

    Total Cases 112

    Excluded Casesa

    0

    Forecasted Cases 0

    Newly Created Cases 0

    a. Cases with a missing value in any

    variable are excluded from the analysis.

    Variable Processing Summary

    Variables

    Dependent Independent

    Kinerjaberdasarkan

    Lingkungan

    Peralatan/Perlengk

    apan

  • 7/27/2019 hasil spss asumsi.docx

    42/117

    Lingkungan apan

    Number of Positive Values 112 112

    Number of Zeros 0 0

    Number of Negative Values 0 0

    Number of Missing Values User-Missing 0 0

    System-Missing 0 0

    Model Summary and Parameter Estimates

    Dependent Variable:Kinerja berdasarkan Lingkungan

    Equation

    Model Summary Parameter Estimates

    R Square F df1 df2 Sig. Constant b1

    Linear .031 3.539 1 110 .063 15.796 -.179

    The independent variable is Peralatan/Perlengkapan.

    * Curve Estimation.TSET NEWVAR=NONE.

    CURVEFIT/VARIABLES=Waktu WITH Pengalaman/CONSTANT/MODEL=LINEAR

    /PLOT NONE.Curve Fit

    Notes

    Output Created 14-Sep-2013 10:37:39

    Comments

    Input Data C:\Users\dell\Documents\rajib.sav

    Active Dataset DataSet1

    Filter

    Weight

    Split File

    N of Rows in Working Data File 112

    Missing Value Handling Definition of Missing User-defined missing values are treated as

    missing.

    Cases Used Cases with a missing value in any variable

    are not used in the analysis.

    Syntax CURVEFIT

  • 7/27/2019 hasil spss asumsi.docx

    43/117

    Syntax CURVEFIT

    /VARIABLES=Waktu WITH Pengalaman

    /CONSTANT

    /MODEL=LINEAR

    /PLOT NONE.

    Resources Processor Time 00:00:00.031

    Elapsed Time 00:00:00.016

    Use From First observation

    To Last observation

    Predict From First Observation following the use period

    To Last observation

    Time Series Settings (TSET) Amount of Output PRINT = DEFAULT

    Saving New Variables NEWVAR = NONE

    Maximum Number of Lags in

    Autocorrelation or Partial

    Autocorrelation Plots

    MXAUTO = 16

    Maximum Number of Lags Per

    Cross-Correlation Plots

    MXCROSS = 7

    Maximum Number of New

    Variables Generated Per

    Procedure

    MXNEWVAR = 60

    Maximum Number of New Cases

    Per ProcedureMXPREDICT = 1000

    Treatment of User-Missing

    ValuesMISSING = EXCLUDE

    Confidence Interval Percentage

    ValueCIN = 95

    Tolerance for Entering Variables

    in Regression Equations

    TOLER = .0001

    Maximum Iterative Parameter

    ChangeCNVERGE = .001

    Method of Calculating Std.

    Errors for AutocorrelationsACFSE = IND

    Length of Seasonal Period Unspecified

    Variable Whose Values Label

    Observations in PlotsUnspecified

    Equations Include CONSTANT

    [DataSet1] C:\Users\dell\Documents\rajib.sav

  • 7/27/2019 hasil spss asumsi.docx

    44/117

    [ ] \ \ \ \ j

    Model Description

    Model Name MOD_19

    Dependent Variable 1 Kinerja berdasarkan Waktu

    Equation 1 Linear

    Independent Variable Pengalaman Kerja

    Constant Included

    Variable Whose Values Label Observations in Plots Unspecified

    Case Processing Summary

    N

    Total Cases 112

    Excluded Casesa

    0

    Forecasted Cases 0

    Newly Created Cases 0

    a. Cases with a missing value in any

    variable are excluded from the analysis.

    Variable Processing Summary

    Variables

    Dependent Independent

    Kinerja

    berdasarkan

    Waktu Pengalaman Kerja

    Number of Positive Values 112 112

    Number of Zeros 0 0

    Number of Negative Values 0 0

    Number of Missing Values User-Missing 0 0

    System-Missing 0 0

    Model Summary and Parameter Estimates

    Dependent Variable:Kinerja berdasarkan Waktu

    Model Summary Parameter Estimates

  • 7/27/2019 hasil spss asumsi.docx

    45/117

    Equation R Square F df1 df2 Sig. Constant b1

    Linear .012 1.311 1 110 .255 19.904 .176

    The independent variable is Pengalaman Kerja.

    * Curve Estimation.TSET NEWVAR=NONE.CURVEFIT/VARIABLES=Kualitas WITH Pengalaman

    /CONSTANT/MODEL=LINEAR

    /PLOT NONE.Curve Fit

    Notes

    Output Created 14-Sep-2013 10:38:02

    Comments

    Input Data C:\Users\dell\Documents\rajib.sav

    Active Dataset DataSet1

    Filter

    Weight

    Split File

    N of Rows in Working Data File 112

    Missing Value Handling Definition of Missing User-defined missing values are treated as

    missing.

    Cases Used Cases with a missing value in any variable

    are not used in the analysis.

    Syntax CURVEFIT

    /VARIABLES=Kualitas WITH Pengalaman

    /CONSTANT

    /MODEL=LINEAR

    /PLOT NONE.

    Resources Processor Time 00:00:00.032

    Elapsed Time 00:00:00.030

    Use From First observation

    To Last observation

    Predict From First Observation following the use period

    To Last observation

    Time Series Settings (TSET) Amount of Output PRINT = DEFAULT

    Saving New Variables NEWVAR = NONE

  • 7/27/2019 hasil spss asumsi.docx

    46/117

    Saving New Variables NEWVAR NONE

    Maximum Number of Lags in

    Autocorrelation or Partial

    Autocorrelation Plots

    MXAUTO = 16

    Maximum Number of Lags Per

    Cross-Correlation PlotsMXCROSS = 7

    Maximum Number of New

    Variables Generated PerProcedure

    MXNEWVAR = 60

    Maximum Number of New Cases

    Per ProcedureMXPREDICT = 1000

    Treatment of User-Missing

    ValuesMISSING = EXCLUDE

    Confidence Interval Percentage

    ValueCIN = 95

    Tolerance for Entering Variables

    in Regression EquationsTOLER = .0001

    Maximum Iterative Parameter

    Change

    CNVERGE = .001

    Method of Calculating Std.

    Errors for AutocorrelationsACFSE = IND

    Length of Seasonal Period Unspecified

    Variable Whose Values Label

    Observations in PlotsUnspecified

    Equations Include CONSTANT

    [DataSet1] C:\Users\dell\Documents\rajib.savModel Description

    Model Name MOD_20

    Dependent Variable 1 Kinerja berdasarkan Kualitas

    Equation 1 Linear

    Independent Variable Pengalaman Kerja

    Constant Included

    Variable Whose Values Label Observations in Plots Unspecified

    Case Processing Summary

    N

  • 7/27/2019 hasil spss asumsi.docx

    47/117

    N

    Total Cases 112

    Excluded Casesa

    0

    Forecasted Cases 0

    Newly Created Cases 0

    a. Cases with a missing value in any

    variable are excluded from the analysis.

    Variable Processing Summary

    Variables

    Dependent Independent

    Kinerja

    berdasarkan

    Kualitas Pengalaman Kerja

    Number of Positive Values 112 112

    Number of Zeros 0 0

    Number of Negative Values 0 0

    Number of Missing Values User-Missing 0 0

    System-Missing 0 0

    Model Summary and Parameter Estimates

    Dependent Variable:Kinerja berdasarkan Kualitas

    Equation

    Model Summary Parameter Estimates

    R Square F df1 df2 Sig. Constant b1

    Linear .002 .189 1 110 .665 22.682 -.057

    The independent variable is Pengalaman Kerja.

    * Curve Estimation.TSET NEWVAR=NONE.CURVEFIT/VARIABLES=K_3 WITH Pengalaman/CONSTANT/MODEL=LINEAR

    /PLOT NONE.

    Curve FitNotes

  • 7/27/2019 hasil spss asumsi.docx

    48/117

    Output Created 14-Sep-2013 10:38:11

    Comments

    Input Data C:\Users\dell\Documents\rajib.sav

    Active Dataset DataSet1

    Filter

    Weight

    Split File

    N of Rows in Working Data File 112

    Missing Value Handling Definition of Missing User-defined missing values are treated as

    missing.

    Cases Used Cases with a missing value in any variable

    are not used in the analysis.

    Syntax CURVEFIT

    /VARIABLES=K_3 WITH Pengalaman

    /CONSTANT

    /MODEL=LINEAR

    /PLOT NONE.

    Resources Processor Time 00:00:00.016

    Elapsed Time 00:00:00.015

    Use From First observation

    To Last observation

    Predict From First Observation following the use period

    To Last observation

    Time Series Settings (TSET) Amount of Output PRINT = DEFAULT

    Saving New Variables NEWVAR = NONE

    Maximum Number of Lags in

    Autocorrelation or Partial

    Autocorrelation Plots

    MXAUTO = 16

    Maximum Number of Lags Per

    Cross-Correlation PlotsMXCROSS = 7

    Maximum Number of New

    Variables Generated Per

    Procedure

    MXNEWVAR = 60

    Maximum Number of New Cases

    Per ProcedureMXPREDICT = 1000

    Treatment of User-Missing

    ValuesMISSING = EXCLUDE

    Confidence Interval PercentageCIN = 95

  • 7/27/2019 hasil spss asumsi.docx

    49/117

    ValueCIN 95

    Tolerance for Entering Variables

    in Regression EquationsTOLER = .0001

    Maximum Iterative Parameter

    ChangeCNVERGE = .001

    Method of Calculating Std.

    Errors for AutocorrelationsACFSE = IND

    Length of Seasonal Period Unspecified

    Variable Whose Values Label

    Observations in PlotsUnspecified

    Equations Include CONSTANT

    [DataSet1] C:\Users\dell\Documents\rajib.savModel Description

    Model Name MOD_21

    Dependent Variable 1 Kinerja berdasarkan K3

    Equation 1 Linear

    Independent Variable Pengalaman Kerja

    Constant Included

    Variable Whose Values Label Observations in Plots Unspecified

    Case Processing Summary

    N

    Total Cases 112

    Excluded Casesa

    0

    Forecasted Cases 0

    Newly Created Cases 0

    a. Cases with a missing value in any

    variable are excluded from the analysis.

    Variable Processing Summary

    VariablesDependent Independent

    Kinerja

  • 7/27/2019 hasil spss asumsi.docx

    50/117

    berdasarkan K3 Pengalaman Kerja

    Number of Positive Values 112 112

    Number of Zeros 0 0

    Number of Negative Values 0 0

    Number of Missing Values User-Missing 0 0

    System-Missing 0 0

    Model Summary and Parameter Estimates

    Dependent Variable:Kinerja berdasarkan K3

    Equation

    Model Summary Parameter Estimates

    R Square F df1 df2 Sig. Constant b1

    Linear .004 .488 1 110 .486 15.390 -.082

    The independent variable is Pengalaman Kerja.

    * Curve Estimation.TSET NEWVAR=NONE.CURVEFIT/VARIABLES=Biaya WITH Pengalaman/CONSTANT/MODEL=LINEAR

    /PLOT NONE.Curve Fit

    Notes

    Output Created 14-Sep-2013 10:38:34

    Comments

    Input Data C:\Users\dell\Documents\rajib.sav

    Active Dataset DataSet1

    Filter

    Weight

    Split File

    N of Rows in Working Data File 112

    Missing Value Handling Definition of Missing User-defined missing values are treated as

    missing.

    Cases Used Cases with a missing value in any variable

    are not used in the analysis.

    Syntax CURVEFIT

    /VARIABLES=Biaya WITH Pengalaman

  • 7/27/2019 hasil spss asumsi.docx

    51/117

    /VARIABLES=Biaya WITH Pengalaman

    /CONSTANT

    /MODEL=LINEAR

    /PLOT NONE.

    Resources Processor Time 00:00:00.032

    Elapsed Time 00:00:00.016

    Use From First observation

    To Last observation

    Predict From First Observation following the use period

    To Last observation

    Time Series Settings (TSET) Amount of Output PRINT = DEFAULT

    Saving New Variables NEWVAR = NONE

    Maximum Number of Lags in

    Autocorrelation or Partial

    Autocorrelation Plots

    MXAUTO = 16

    Maximum Number of Lags Per

    Cross-Correlation Plots

    MXCROSS = 7

    Maximum Number of New

    Variables Generated Per

    Procedure

    MXNEWVAR = 60

    Maximum Number of New Cases

    Per ProcedureMXPREDICT = 1000

    Treatment of User-Missing

    ValuesMISSING = EXCLUDE

    Confidence Interval Percentage

    ValueCIN = 95

    Tolerance for Entering Variables

    in Regression Equations

    TOLER = .0001

    Maximum Iterative Parameter

    ChangeCNVERGE = .001

    Method of Calculating Std.

    Errors for AutocorrelationsACFSE = IND

    Length of Seasonal Period Unspecified

    Variable Whose Values Label

    Observations in PlotsUnspecified

    Equations Include CONSTANT

    [DataSet1] C:\Users\dell\Documents\rajib.sav

  • 7/27/2019 hasil spss asumsi.docx

    52/117

    Model Description

    Model Name MOD_22

    Dependent Variable 1 Kinerja berdasarkan Biaya

    Equation 1 Linear

    Independent Variable Pengalaman Kerja

    Constant Included

    Variable Whose Values Label Observations in Plots Unspecified

    Case Processing Summary

    N

    Total Cases 112

    Excluded Casesa

    0

    Forecasted Cases 0

    Newly Created Cases 0

    a. Cases with a missing value in any

    variable are excluded from the analysis.

    Variable Processing Summary

    Variables

    Dependent Independent

    Kinerja

    berdasarkan Biaya Pengalaman Kerja

    Number of Positive Values 112 112

    Number of Zeros 0 0

    Number of Negative Values 0 0

    Number of Missing Values User-Missing 0 0

    System-Missing 0 0

    Model Summary and Parameter Estimates

    Dependent Variable:Kinerja berdasarkan Biaya

    Equation

    Model Summary Parameter Estimates

    R Square F df1 df2 Sig. Constant b1

    Linear .083 9.966 1 110 .002 30.384 -.440

  • 7/27/2019 hasil spss asumsi.docx

    53/117

    The independent variable is Pengalaman Kerja.

    * Curve Estimation.TSET NEWVAR=NONE.CURVEFIT/VARIABLES=Lingk WITH Pengalaman/CONSTANT/MODEL=LINEAR

    /PLOT NONE.Curve Fit

    Notes

    Output Created 14-Sep-2013 10:38:48

    Comments

    Input Data C:\Users\dell\Documents\rajib.sav

    Active Dataset DataSet1

    Filter

    Weight

    Split File

    N of Rows in Working Data File 112

    Missing Value Handling Definition of Missing User-defined missing values are treated as

    missing.

    Cases Used Cases with a missing value in any variable

    are not used in the analysis.

    Syntax CURVEFIT

    /VARIABLES=Lingk WITH Pengalaman

    /CONSTANT

    /MODEL=LINEAR

    /PLOT NONE.

    Resources Processor Time 00:00:00.031

    Elapsed Time 00:00:00.015

    Use From First observation

    To Last observation

    Predict From First Observation following the use period

    To Last observation

    Time Series Settings (TSET) Amount of Output PRINT = DEFAULT

    Saving New Variables NEWVAR = NONE

    Maximum Number of Lags in

    Autocorrelation or Partial MXAUTO = 16

  • 7/27/2019 hasil spss asumsi.docx

    54/117

    Autocorrelation or Partial

    Autocorrelation Plots

    MXAUTO = 16

    Maximum Number of Lags Per

    Cross-Correlation PlotsMXCROSS = 7

    Maximum Number of New

    Variables Generated Per

    Procedure

    MXNEWVAR = 60

    Maximum Number of New Cases

    Per ProcedureMXPREDICT = 1000

    Treatment of User-Missing

    ValuesMISSING = EXCLUDE

    Confidence Interval Percentage

    ValueCIN = 95

    Tolerance for Entering Variables

    in Regression EquationsTOLER = .0001

    Maximum Iterative Parameter

    ChangeCNVERGE = .001

    Method of Calculating Std.

    Errors for AutocorrelationsACFSE = IND

    Length of Seasonal Period Unspecified

    Variable Whose Values Label

    Observations in PlotsUnspecified

    Equations Include CONSTANT

    [DataSet1] C:\Users\dell\Documents\rajib.savModel Description

    Model Name MOD_23

    Dependent Variable 1 Kinerja berdasarkan Lingkungan

    Equation 1 Linear

    Independent Variable Pengalaman Kerja

    Constant Included

    Variable Whose Values Label Observations in Plots Unspecified

    Case Processing Summary

    N

    Total Cases 112

    E l d d Ca

    0

  • 7/27/2019 hasil spss asumsi.docx

    55/117

    Excluded Casesa

    0

    Forecasted Cases 0

    Newly Created Cases 0

    a. Cases with a missing value in any

    variable are excluded from the analysis.

    Variable Processing Summary

    Variables

    Dependent Independent

    Kinerja

    berdasarkan

    Lingkungan Pengalaman Kerja

    Number of Positive Values 112 112

    Number of Zeros 0 0

    Number of Negative Values 0 0

    Number of Missing Values User-Missing 0 0

    System-Missing 0 0

    Model Summary and Parameter Estimates

    Dependent Variable:Kinerja berdasarkan Lingkungan

    Equation

    Model Summary Parameter Estimates

    R Square F df1 df2 Sig. Constant b1

    Linear .004 .496 1 110 .483 14.163 -.088

    The independent variable is Pengalaman Kerja.

    * Curve Estimation.TSET NEWVAR=NONE.CURVEFIT/VARIABLES=Waktu WITH Kemampuan/CONSTANT/MODEL=LINEAR

    /PLOT NONE.Curve Fit

  • 7/27/2019 hasil spss asumsi.docx

    56/117

    Treatment of User-Missing

    ValuesMISSING = EXCLUDE

    Confidence Interval Percentage

    ValueCIN = 95

  • 7/27/2019 hasil spss asumsi.docx

    57/117

    Tolerance for Entering Variables

    in Regression EquationsTOLER = .0001

    Maximum Iterative Parameter

    ChangeCNVERGE = .001

    Method of Calculating Std.

    Errors for AutocorrelationsACFSE = IND

    Length of Seasonal Period Unspecified

    Variable Whose Values Label

    Observations in PlotsUnspecified

    Equations Include CONSTANT

    [DataSet1] C:\Users\dell\Documents\rajib.savModel Description

    Model Name MOD_24

    Dependent Variable 1 Kinerja berdasarkan Waktu

    Equation 1 Linear

    Independent Variable Sisa Kemampuan Biaya

    Constant Included

    Variable Whose Values Label Observations in Plots Unspecified

    Case Processing Summary

    N

    Total Cases 112

    Excluded Casesa

    0

    Forecasted Cases 0

    Newly Created Cases 0

    a. Cases with a missing value in any

    variable are excluded from the analysis.

    Variable Processing Summary

    VariablesDependent Independent

    Kinerja

    berdasarkan Sisa Kemampuan

  • 7/27/2019 hasil spss asumsi.docx

    58/117

    Waktu Biaya

    Number of Positive Values 112 112

    Number of Zeros 0 0

    Number of Negative Values 0 0

    Number of Missing Values User-Missing 0 0

    System-Missing 0 0

    Model Summary and Parameter Estimates

    Dependent Variable:Kinerja berdasarkan Waktu

    Equation

    Model Summary Parameter Estimates

    R Square F df1 df2 Sig. Constant b1

    Linear .005 .568 1 110 .453 22.838 -.316

    The independent variable is Sisa Kemampuan Biaya.

    * Curve Estimation.TSET NEWVAR=NONE.CURVEFIT/VARIABLES=Kualitas WITH Kemampuan/CONSTANT/MODEL=LINEAR

    /PLOT NONE.Curve Fit

    Notes

    Output Created 14-Sep-2013 10:40:09

    Comments

    Input Data C:\Users\dell\Documents\rajib.sav

    Active Dataset DataSet1

    Filter

    Weight

    Split File

    N of Rows in Working Data File 112

    Missing Value Handling Definition of Missing User-defined missing values are treated as

    missing.

    Cases Used Cases with a missing value in any variable

    are not used in the analysis.

  • 7/27/2019 hasil spss asumsi.docx

    59/117

    Syntax CURVEFIT

    /VARIABLES=Kualitas WITH Kemampuan

    /CONSTANT

    /MODEL=LINEAR

    /PLOT NONE.

    Resources Processor Time 00:00:00.032

    Elapsed Time 00:00:00.016

    Use From First observation

    To Last observation

    Predict From First Observation following the use period

    To Last observation

    Time Series Settings (TSET) Amount of Output PRINT = DEFAULT

    Saving New Variables NEWVAR = NONE

    Maximum Number of Lags in

    Autocorrelation or Partial

    Autocorrelation Plots

    MXAUTO = 16

    Maximum Number of Lags Per

    Cross-Correlation PlotsMXCROSS = 7

    Maximum Number of New

    Variables Generated Per

    Procedure

    MXNEWVAR = 60

    Maximum Number of New Cases

    Per ProcedureMXPREDICT = 1000

    Treatment of User-Missing

    ValuesMISSING = EXCLUDE

    Confidence Interval Percentage

    ValueCIN = 95

    Tolerance for Entering Variables

    in Regression EquationsTOLER = .0001

    Maximum Iterative Parameter

    ChangeCNVERGE = .001

    Method of Calculating Std.

    Errors for AutocorrelationsACFSE = IND

    Length of Seasonal Period Unspecified

    Variable Whose Values Label

    Observations in PlotsUnspecified

    Equations Include CONSTANT

  • 7/27/2019 hasil spss asumsi.docx

    60/117

    [DataSet1] C:\Users\dell\Documents\rajib.savModel Description

    Model Name MOD_25

    Dependent Variable 1 Kinerja berdasarkan Kualitas

    Equation 1 Linear

    Independent Variable Sisa Kemampuan Biaya

    Constant Included

    Variable Whose Values Label Observations in Plots Unspecified

    Case Processing Summary

    N

    Total Cases 112

    Excluded Casesa 0

    Forecasted Cases 0

    Newly Created Cases 0

    a. Cases with a missing value in any

    variable are excluded from the analysis.

    Variable Processing Summary

    Variables

    Dependent Independent

    Kinerja

    berdasarkan

    Kualitas

    Sisa Kemampuan

    Biaya

    Number of Positive Values 112 112

    Number of Zeros 0 0

    Number of Negative Values 0 0

    Number of Missing Values User-Missing 0 0

    System-Missing 0 0

    Model Summary and Parameter Estimates

    Dependent Variable:Kinerja berdasarkan Kualitas

  • 7/27/2019 hasil spss asumsi.docx

    61/117

    Equation

    Model Summary Parameter Estimates

    R Square F df1 df2 Sig. Constant b1

    Linear .007 .778 1 110 .380 23.221 -.313

    The independent variable is Sisa Kemampuan Biaya.

    * Curve Estimation.TSET NEWVAR=NONE.CURVEFIT/VARIABLES=K_3 WITH Kemampuan/CONSTANT/MODEL=LINEAR

    /PLOT NONE.Curve Fit

    Notes

    Output Created 14-Sep-2013 10:40:24

    Comments

    Input Data C:\Users\dell\Documents\rajib.sav

    Active Dataset DataSet1

    Filter

    Weight

    Split File

    N of Rows in Working Data File 112

    Missing Value Handling Definition of Missing User-defined missing values are treated as

    missing.

    Cases Used Cases with a missing value in any variable

    are not used in the analysis.

    Syntax CURVEFIT

    /VARIABLES=K_3 WITH Kemampuan

    /CONSTANT

    /MODEL=LINEAR

    /PLOT NONE.

    Resources Processor Time 00:00:00.015

    Elapsed Time 00:00:00.015

    Use From First observation

    To Last observation

    Predict From First Observation following the use period

    To Last observation

  • 7/27/2019 hasil spss asumsi.docx

    62/117

    Time Series Settings (TSET) Amount of Output PRINT = DEFAULT

    Saving New Variables NEWVAR = NONE

    Maximum Number of Lags in

    Autocorrelation or Partial

    Autocorrelation Plots

    MXAUTO = 16

    Maximum Number of Lags Per

    Cross-Correlation PlotsMXCROSS = 7

    Maximum Number of New

    Variables Generated Per

    Procedure

    MXNEWVAR = 60

    Maximum Number of New Cases

    Per ProcedureMXPREDICT = 1000

    Treatment of User-Missing

    ValuesMISSING = EXCLUDE

    Confidence Interval Percentage

    ValueCIN = 95

    Tolerance for Entering Variablesin Regression Equations

    TOLER = .0001

    Maximum Iterative Parameter

    ChangeCNVERGE = .001

    Method of Calculating Std.

    Errors for AutocorrelationsACFSE = IND

    Length of Seasonal Period Unspecified

    Variable Whose Values Label

    Observations in PlotsUnspecified

    Equations Include CONSTANT

    [DataSet1] C:\Users\dell\Documents\rajib.savModel Description

    Model Name MOD_26

    Dependent Variable 1 Kinerja berdasarkan K3

    Equation 1 Linear

    Independent Variable Sisa Kemampuan Biaya

    Constant Included

    Variable Whose Values Label Observations in Plots Unspecified

  • 7/27/2019 hasil spss asumsi.docx

    63/117

    Case Processing Summary

    N

    Total Cases 112

    Excluded Casesa

    0

    Forecasted Cases 0

    Newly Created Cases 0

    a. Cases with a missing value in any

    variable are excluded from the analysis.

    Variable Processing Summary

    Variables

    Dependent Independent

    Kinerja

    berdasarkan K3

    Sisa Kemampuan

    Biaya

    Number of Positive Values 112 112

    Number of Zeros 0 0

    Number of Negative Values 0 0

    Number of Missing Values User-Missing 0 0

    System-Missing 0 0

    Model Summary and Parameter Estimates

    Dependent Variable:Kinerja berdasarkan K3

    Equation

    Model Summary Parameter Estimates

    R Square F df1 df2 Sig. Constant b1

    Linear .000 .004 1 110 .951 14.625 -.020

    The independent variable is Sisa Kemampuan Biaya.

    * Curve Estimation.TSET NEWVAR=NONE.CURVEFIT/VARIABLES=Biaya WITH Kemampuan/CONSTANT

    /MODEL=LINEAR

    /PLOT NONE.Curve Fit

  • 7/27/2019 hasil spss asumsi.docx

    64/117

    Notes

    Output Created 14-Sep-2013 10:40:39

    Comments

    Input Data C:\Users\dell\Documents\rajib.sav

    Active Dataset DataSet1

    Filter

    Weight

    Split File

    N of Rows in Working Data File 112

    Missing Value Handling Definition of Missing User-defined missing values are treated as

    missing.

    Cases Used Cases with a missing value in any variable

    are not used in the analysis.

    Syntax CURVEFIT

    /VARIABLES=Biaya WITH Kemampuan

    /CONSTANT

    /MODEL=LINEAR

    /PLOT NONE.

    Resources Processor Time 00:00:00.016

    Elapsed Time 00:00:00.016

    Use From First observation

    To Last observation

    Predict From First Observation following the use period

    To Last observation

    Time Series Settings (TSET) Amount of Output PRINT = DEFAULT

    Saving New Variables NEWVAR = NONE

    Maximum Number of Lags in

    Autocorrelation or Partial

    Autocorrelation Plots

    MXAUTO = 16

    Maximum Number of Lags Per

    Cross-Correlation PlotsMXCROSS = 7

    Maximum Number of New

    Variables Generated Per

    Procedure

    MXNEWVAR = 60

    Maximum Number of New Cases

    Per ProcedureMXPREDICT = 1000

  • 7/27/2019 hasil spss asumsi.docx

    65/117

    Treatment of User-Missing

    ValuesMISSING = EXCLUDE

    Confidence Interval Percentage

    ValueCIN = 95

    Tolerance for Entering Variables

    in Regression Equations

    TOLER = .0001

    Maximum Iterative Parameter

    ChangeCNVERGE = .001

    Method of Calculating Std.

    Errors for AutocorrelationsACFSE = IND

    Length of Seasonal Period Unspecified

    Variable Whose Values Label

    Observations in PlotsUnspecified

    Equations Include CONSTANT

    [DataSet1] C:\Users\dell\Documents\rajib.savModel Description

    Model Name MOD_27

    Dependent Variable 1 Kinerja berdasarkan Biaya

    Equation 1 Linear

    Independent Variable Sisa Kemampuan Biaya

    Constant Included

    Variable Whose Values Label Observations in Plots Unspecified

    Case Processing Summary

    N

    Total Cases 112

    Excluded Casesa

    0

    Forecasted Cases 0

    Newly Created Cases 0

    Case Processing Summary

    N

    Total Cases 112

    Excluded Casesa

    0

    Forecasted Cases 0

  • 7/27/2019 hasil spss asumsi.docx

    66/117

    Forecasted Cases 0

    Newly Created Cases 0

    a. Cases with a missing value in any

    variable are excluded from the analysis.

    Variable Processing Summary

    Variables

    Dependent Independent

    Kinerja

    berdasarkan Biaya

    Sisa Kemampuan

    Biaya

    Number of Positive Values 112 112

    Number of Zeros 0 0

    Number of Negative Values 0 0

    Number of Missing Values User-Missing 0 0

    System-Missing 0 0

    Model Summary and Parameter Estimates

    Dependent Variable:Kinerja berdasarkan Biaya

    Equation

    Model Summary Parameter Estimates

    R Square F df1 df2 Sig. Constant b1

    Linear .011 1.262 1 110 .264 27.472 -.440

    The independent variable is Sisa Kemampuan Biaya.

    * Curve Estimation.TSET NEWVAR=NONE.CURVEFIT/VARIABLES=Lingk WITH Kemampuan/CONSTANT/MODEL=LINEAR

    /PLOT NONE.Curve Fit

    Notes

    Output Created 14-Sep-2013 10:40:58

    Comments

    Input Data C:\Users\dell\Documents\rajib.sav

    Active Dataset DataSet1

  • 7/27/2019 hasil spss asumsi.docx

    67/117

    Filter

    Weight

    Split File

    N of Rows in Working Data File 112

    Missing Value Handling Definition of Missing User-defined missing values are treated asmissing.

    Cases Used Cases with a missing value in any variable

    are not used in the analysis.

    Syntax CURVEFIT

    /VARIABLES=Lingk WITH Kemampuan

    /CONSTANT

    /MODEL=LINEAR

    /PLOT NONE.

    Resources Processor Time 00:00:00.031

    Elapsed Time 00:00:00.016

    Use From First observation

    To Last observation

    Predict From First Observation following the use period

    To Last observation

    Time Series Settings (TSET) Amount of Output PRINT = DEFAULT

    Saving New Variables NEWVAR = NONE

    Maximum Number of Lags in

    Autocorrelation or Partial

    Autocorrelation Plots

    MXAUTO = 16

    Maximum Number of Lags Per

    Cross-Correlation Plots MXCROSS = 7

    Maximum Number of New

    Variables Generated Per

    Procedure

    MXNEWVAR = 60

    Maximum Number of New Cases

    Per ProcedureMXPREDICT = 1000

    Treatment of User-Missing

    ValuesMISSING = EXCLUDE

    Confidence Interval Percentage

    ValueCIN = 95

    Tolerance for Entering Variables

    in Regression EquationsTOLER = .0001

    Maximum Iterative Parameter

    ChCNVERGE = .001

  • 7/27/2019 hasil spss asumsi.docx

    68/117

    Change

    Method of Calculating Std.

    Errors for AutocorrelationsACFSE = IND

    Length of Seasonal Period Unspecified

    Variable Whose Values Label

    Observations in PlotsUnspecified

    Equations Include CONSTANT

    [DataSet1] C:\Users\dell\Documents\rajib.savModel Description

    Model Name MOD_28

    Dependent Variable 1 Kinerja berdasarkan Lingkungan

    Equation 1 Linear

    Independent Variable Sisa Kemampuan Biaya

    Constant Included

    Variable Whose Values Label Observations in Plots Unspecified

    Case Processing Summary

    N

    Total Cases 112

    Excluded Casesa

    0

    Forecasted Cases 0

    Newly Created Cases 0

    a. Cases with a missing value in any

    variable are excluded from the analysis.

    Variable Processing Summary

    Variables

    Dependent Independent

    Kinerjaberdasarkan

    Lingkungan

    Sisa Kemampuan

    Biaya

    Number of Positive Values 112 112

    Number of Zeros 0 0

  • 7/27/2019 hasil spss asumsi.docx

    69/117

    Number of Negative Values 0 0

    Number of Missing Values User-Missing 0 0

    System-Missing 0 0

    Model Summary and Parameter Estimates

    Dependent Variable:Kinerja berdasarkan Lingkungan

    Equation

    Model Summary Parameter Estimates

    R Square F df1 df2 Sig. Constant b1

    Linear .008 .906 1 110 .343 14.417 -.320

    The independent variable is Sisa Kemampuan Biaya.

    * Curve Estimation.TSET NEWVAR=NONE.CURVEFIT

    /VARIABLES=Waktu WITH Mutu/CONSTANT/MODEL=LINEAR

    /PLOT NONE.Curve Fit

    Notes

    Output Created 14-Sep-2013 10:41:41

    Comments

    Input Data C:\Users\dell\Documents\rajib.sav

    Active Dataset DataSet1

    Filter

    Weight

    Split File

    N of Rows in Working Data File 112

    Missing Value Handling Definition of Missing User-defined missing values are treated as

    missing.

  • 7/27/2019 hasil spss asumsi.docx

    70/117

    [DataSet1] C:\Users\dell\Documents\rajib.sav

    Model Description

    Model Name MOD 29

  • 7/27/2019 hasil spss asumsi.docx

    71/117

    Model Name MOD_29

    Dependent Variable 1 Kinerja berdasarkan Waktu

    Equation 1 Linear

    Independent Variable Manajemen Mutu

    Constant Included

    Variable Whose Values Label Observations in Plots Unspecified

    Case Processing Summary

    N

    Total Cases 112

    Excluded Casesa

    0

    Forecasted Cases 0

    Newly Created Cases 0

    a. Cases with a missing value in anyvariable are excluded from the analysis.

    Variable Processing Summary

    Variables

    Dependent Independent

    Kinerja

    berdasarkan

    Waktu Manajemen Mutu

    Number of Positive Values 112 112

    Number of Zeros 0 0

    Number of Negative Values 0 0

    Number of Missing Values User-Missing 0 0

    System-Missing 0 0

    Model Summary and Parameter Estimates

    Dependent Variable:Kinerja berdasarkan Waktu

    Equation

    Model Summary Parameter Estimates

    R Square F df1 df2 Sig. Constant b1

    Linear .044 5.025 1 110 .027 25.368 -.337

    The independent variable is Manajemen Mutu.

  • 7/27/2019 hasil spss asumsi.docx

    72/117

    * Curve Estimation.TSET NEWVAR=NONE.CURVEFIT/VARIABLES=Kualitas WITH Mutu/CONSTANT

    /MODEL=LINEAR

    /PLOT NONE.Curve Fit

    Notes

    Output Created 14-Sep-2013 10:42:02

    Comments

    Input Data C:\Users\dell\Documents\rajib.sav

    Active Dataset DataSet1

    Filter

    Weight

    Split File

    N of Rows in Working Data File 112

    Missing Value Handling Definition of Missing User-defined missing values are treated as

    missing.

    Cases Used Cases with a missing value in any variable

    are not used in the analysis.

    Syntax CURVEFIT

    /VARIABLES=Kualitas WITH Mutu

    /CONSTANT

    /MODEL=LINEAR/PLOT NONE.

    Resources Processor Time 00:00:00.031

    Elapsed Time 00:00:00.016

    Use From First observation

    To Last observation

    Predict From First Observation following the use period

    To Last observation

    Time Series Settings (TSET) Amount of Output PRINT = DEFAULT

    Saving New Variables NEWVAR = NONE

    Maximum Number of Lags in

    Autocorrelation or Partial

    Autocorrelation Plots

    MXAUTO = 16

  • 7/27/2019 hasil spss asumsi.docx

    73/117

    Maximum Number of Lags Per

    Cross-Correlation PlotsMXCROSS = 7

    Maximum Number of New

    Variables Generated Per

    Procedure

    MXNEWVAR = 60

    Maximum Number of New Cases

    Per ProcedureMXPREDICT = 1000

    Treatment of User-Missing

    ValuesMISSING = EXCLUDE

    Confidence Interval Percentage

    ValueCIN = 95

    Tolerance for Entering Variables

    in Regression EquationsTOLER = .0001

    Maximum Iterative Parameter

    ChangeCNVERGE = .001

    Method of Calculating Std.

    Errors for AutocorrelationsACFSE = IND

    Length of Seasonal Period Unspecified

    Variable Whose Values Label

    Observations in PlotsUnspecified

    Equations Include CONSTANT

    [DataSet1] C:\Users\dell\Documents\rajib.savModel Description

    Model Name MOD_30

    Dependent Variable 1 Kinerja berdasarkan Kualitas

    Equation 1 Linear

    Independent Variable Manajemen Mutu

    Constant Included

    Variable Whose Values Label Observations in Plots Unspecified

    Case Processing Summary

    N

    Total Cases 112

    Excluded Casesa

    0

  • 7/27/2019 hasil spss asumsi.docx

    74/117

    Forecasted Cases 0

    Newly Created Cases 0

    a. Cases with a missing value in any

    variable are excluded from the analysis.

    Variable Processing Summary

    Variables

    Dependent Independent

    Kinerja

    berdasarkan

    Kualitas Manajemen Mutu

    Number of Positive Values 112 112

    Number of Zeros 0 0

    Number of Negative Values 0 0

    Number of Missing Values User-Missing 0 0

    System-Missing 0 0

    Model Summary and Parameter Estimates

    Dependent Variable:Kinerja berdasarkan Kualitas

    Equation

    Model Summary Parameter Estimates

    R Square F df1 df2 Sig. Constant b1

    Linear .003 .352 1 110 .554 22.938 -.077

    The independent variable is Manajemen Mutu.

    * Curve Estimation.TSET NEWVAR=NONE.CURVEFIT/VARIABLES=K_3 WITH Mutu/CONSTANT/MODEL=LINEAR

    /PLOT NONE.

    Curve FitNotes

    Output Created 14-Sep-2013 10:42:16

    Comments

    Input Data C:\Users\dell\Documents\rajib sav

  • 7/27/2019 hasil spss asumsi.docx

    75/117

    Input Data C:\Users\dell\Documents\rajib.sav

    Active Dataset DataSet1

    Filter

    Weight

    Split File

    N of Rows in Working Data File 112

    Missing Value Handling Definition of Missing User-defined missing values are treated as

    missing.

    Cases Used Cases with a missing value in any variable

    are not used in the analysis.

    Syntax CURVEFIT

    /VARIABLES=K_3 WITH Mutu

    /CONSTANT

    /MODEL=LINEAR

    /PLOT NONE.

    Resources Processor Time 00:00:00.031

    Elapsed Time 00:00:00.015

    Use From First observation

    To Last observation

    Predict From First Observation following the use period

    To Last observation

    Time Series Settings (TSET) Amount of Output PRINT = DEFAULT

    Saving New Variables NEWVAR = NONE

    Maximum Number of Lags in

    Autocorrelation or Partial

    Autocorrelation Plots

    MXAUTO = 16

    Maximum Number of Lags Per

    Cross-Correlation PlotsMXCROSS = 7

    Maximum Number of New

    Variables Generated Per

    Procedure

    MXNEWVAR = 60

    Maximum Number of New Cases

    Per ProcedureMXPREDICT = 1000

    Treatment of User-Missing

    ValuesMISSING = EXCLUDE

    Confidence Interval Percentage

    ValueCIN = 95

    Tolerance for Entering Variables

    in Regression EquationsTOLER = .0001

  • 7/27/2019 hasil spss asumsi.docx

    76/117

    Maximum Iterative Parameter

    ChangeCNVERGE = .001

    Method of Calculating Std.

    Errors for AutocorrelationsACFSE = IND

    Length of Seasonal Period Unspecified

    Variable Whose Values Label

    Observations in PlotsUnspecified

    Equations Include CONSTANT

    [DataSet1] C:\Users\dell\Documents\rajib.savModel Description

    Model Name MOD_31

    Dependent Variable 1 Kinerja berdasarkan K3

    Equation 1 Linear

    Independent Variable Manajemen Mutu

    Constant Included

    Variable Whose Values Label Observations in Plots Unspecified

    Case Processing Summary

    N

    Total Cases 112

    Excluded Casesa

    0

    Forecasted Cases 0

    Newly Created Cases 0

    a. Cases with a missing value in any

    variable are excluded from the analysis.

    Variable Processing Summary

    VariablesDependent Independent

    Kinerja

    berdasarkan K3 Manajemen Mutu

    Number of Positive Values 112 112

    Number of Zeros 0 0

  • 7/27/2019 hasil spss asumsi.docx

    77/117

    Number of Negative Values 0 0

    Number of Missing Values User-Missing 0 0

    System-Missing 0 0

    Model Summary and Parameter Estimates

    Dependent Variable:Kinerja berdasarkan K3

    Equation

    Model Summary Parameter Estimates

    R Square F df1 df2 Sig. Constant b1

    Linear .028 3.156 1 110 .078 16.772 -.204

    The independent variable is Manajemen Mutu.

    * Curve Estimation.

    TSET NEWVAR=NONE.CURVEFIT/VARIABLES=Biaya WITH Mutu/CONSTANT/MODEL=LINEAR

    /PLOT NONE.Curve Fit

    Notes

    Output Created 14-Sep-2013 10:42:32

    Comments

    Input Data C:\Users\dell\Documents\rajib.sav

    Active Dataset DataSet1

    Filter

    Weight

    Split File

    N of Rows in Working Data File 112

    Missing Value Handling Definition of Missing User-defined missing values are treated as

    missing.

    Cases Used Cases with a missing value in any variable

    are not used in the analysis.

    Syntax CURVEFIT

    /VARIABLES=Biaya WITH Mutu

    /CONSTANT

    /MODEL=LINEAR

    /PLOT NONE.

  • 7/27/2019 hasil spss asumsi.docx

    78/117

    Resources Processor Time 00:00:00.031

    Elapsed Time 00:00:00.016

    Use From First observation

    To Last observation

    Predict From First Observation following the use period

    To Last observation

    Time Series Settings (TSET) Amount of Output PRINT = DEFAULT

    Saving New Variables NEWVAR = NONE

    Maximum Number of Lags in

    Autocorrelation or Partial

    Autocorrelation Plots

    MXAUTO = 16

    Maximum Number of Lags Per

    Cross-Correlation PlotsMXCROSS = 7

    Maximum Number of New

    Variables Generated Per

    Procedure

    MXNEWVAR = 60

    Maximum Number of New Cases

    Per ProcedureMXPREDICT = 1000

    Treatment of User-Missing

    ValuesMISSING = EXCLUDE

    Confidence Interval Percentage

    ValueCIN = 95

    Tolerance for Entering Variables

    in Regression EquationsTOLER = .0001

    Maximum Iterative Parameter

    ChangeCNVERGE = .001

    Method of Calculating Std.

    Errors for AutocorrelationsACFSE = IND

    Length of Seasonal Period Unspecified

    Variable Whose Values Label

    Observations in PlotsUnspecified

    Equations Include CONSTANT

    [DataSet1] C:\Users\dell\Documents\rajib.sav

    Model Description

    Model Name MOD_32

  • 7/27/2019 hasil spss asumsi.docx

    79/117

    Dependent Variable 1 Kinerja berdasarkan Biaya

    Equation 1 Linear

    Independent Variable Manajemen Mutu

    Constant Included

    Variable Whose Values Label Observations in Plots Unspecified

    Case Processing Summary

    N

    Total Cases 112

    Excluded Casesa

    0

    Forecasted Cases 0

    Newly Created Cases 0

    a. Cases with a missing value in any

    variable are excluded from the analysis.

    Variable Processing Summary

    Variables

    Dependent Independent

    Kinerja

    berdasarkan Biaya Manajemen Mutu

    Number of Positive Values 112 112

    Number of Zeros 0 0

    Number of Negative Values 0 0

    Number of Missing Values User-Missing 0 0

    System-Missing 0 0

    Model Summary and Parameter Estimates

    Dependent Variable:Kinerja berdasarkan Biaya

    Equation

    Model Summary Parameter Estimates

    R Square F df1 df2 Sig. Constant b1

    Linear .003 .361 1 110 .549 24.952 .087

    The independent variable is Manajemen Mutu.

    * Curve Estimation.

  • 7/27/2019 hasil spss asumsi.docx

    80/117

    TSET NEWVAR=NONE.CURVEFIT/VARIABLES=Lingk WITH Mutu/CONSTANT/MODEL=LINEAR

    /PLOT NONE.Curve Fit

    Notes

    Output Created 14-Sep-2013 10:42:54

    Comments

    Input Data C:\Users\dell\Documents\rajib.sav

    Active Dataset DataSet1

    Filter

    Weight

    Split File

    N of Rows in Working Data File 112

    Missing Value Handling Definition of Missing User-defined missing values are treated as

    missing.

    Cases Used Cases with a missing value in any variable

    are not used in the analysis.

    Syntax CURVEFIT

    /VARIABLES=Lingk WITH Mutu

    /CONSTANT

    /MODEL=LINEAR

    /PLOT NONE.

    Resources Processor Time 00:00:00.031

    Elapsed Time 00:00:00.014

    Use From First observation

    To Last observation

    Predict From First Observation following the use period

    To Last observation

    Time Series Settings (TSET) Amount of Output PRINT = DEFAULT

    Saving New Variables NEWVAR = NONE

    Maximum Number of Lags in

    Autocorrelation or Partial

    Autocorrelation Plots

    MXAUTO = 16

    Maximum Number of Lags Per

    Cross-Correlation PlotsMXCROSS = 7

  • 7/27/2019 hasil spss asumsi.docx

    81/117

    Maximum Number of New

    Variables Generated Per

    Procedure

    MXNEWVAR = 60

    Maximum Number of New CasesPer Procedure

    MXPREDICT = 1000

    Treatment of User-Missing

    ValuesMISSING = EXCLUDE

    Confidence Interval Percentage

    ValueCIN = 95

    Tolerance for Entering Variables

    in Regression EquationsTOLER = .0001

    Maximum Iterative Parameter

    ChangeCNVERGE = .001

    Method of Calculating Std.

    Errors for Autocorrelations

    ACFSE = IND

    Length of Seasonal Period Unspecified

    Variable Whose Values Label

    Observations in PlotsUnspecified

    Equations Include CONSTANT

    [DataSet1] C:\Users\dell\Documents\rajib.savModel Description

    Model Name MOD_33

    Dependent Variable 1 Kinerja berdasarkan Lingkungan

    Equation 1 Linear

    Independent Variable Manajemen Mutu

    Constant Included

    Variable Whose Values Label Observations in Plots Unspecified

  • 7/27/2019 hasil spss asumsi.docx

    82/117

    Notes

    Output Created 14-Sep-2013 10:43:14

    Comments

    Input Data C:\Users\dell\Documents\rajib.sav

    Active Dataset DataSet1

    Filt

  • 7/27/2019 hasil spss asumsi.docx

    83/117

    Filter

    Weight

    Split File

    N of Rows in Working Data File 112

    Missing Value Handling Definition of Missing User-defined missing values are treated as

    missing.

    Cases Used Cases with a missing value in any variable

    are not used in the analysis.

    Syntax CURVEFIT

    /VARIABLES=Waktu WITH Keselamatan

    /CONSTANT

    /MODEL=LINEAR

    /PLOT NONE.

    Resources Processor Time 00:00:00.032

    Elapsed Time 00:00:00.016

    Use From First observation

    To Last observation

    Predict From First Observation following the use period

    To Last observation

    Time Series Settings (TSET) Amount of Output PRINT = DEFAULT

    Saving New Variables NEWVAR = NONE

    Maximum Number of Lags in

    Autocorrelation or Partial

    Autocorrelation Plots

    MXAUTO = 16

    Maximum Number of Lags Per

    Cross-Correlation PlotsMXCROSS = 7

    Maximum Number of New

    Variables Generated Per

    Procedure

    MXNEWVAR = 60

    Maximum Number of New Cases

    Per ProcedureMXPREDICT = 1000

    Treatment of User-Missing

    ValuesMISSING = EXCLUDE

    Confidence Interval Percentage

    ValueCIN = 95

    Tolerance for Entering Variables

    in Regression EquationsTOLER = .0001

    Maximum Iterative ParameterCNVERGE = 001

  • 7/27/2019 hasil spss asumsi.docx

    84/117

    ChangeCNVERGE .001

    Method of Calculating Std.

    Errors for AutocorrelationsACFSE = IND

    Length of Seasonal Period Unspecified

    Variable Whose Values Label

    Observations in PlotsUnspecified

    Equations Include CONSTANT

    [DataSet1] C:\Users\dell\Documents\rajib.savModel Description

    Model Name MOD_34

    Dependent Variable 1 Kinerja berdasarkan Waktu

    Equation 1 Linear

    Independent Variable Keselamatan Kerja

    Constant Included

    Variable Whose Values Label Observations in Plots Unspecified

    Case Processing Summary

    N

    Total Cases 112

    Excluded Casesa

    0

    Forecasted Cases 0

    Newly Created Cases 0

    a. Cases with a missing value in any

    variable are excluded from the analysis.

    Variable Processing Summary

  • 7/27/2019 hasil spss asumsi.docx

    85/117

  • 7/27/2019 hasil spss asumsi.docx

    86/117

    Variable Whose Values Label

    Observations in PlotsUnspecified

    Equations Include CONSTANT

    [DataSet1] C:\Users\dell\Documents\rajib.sav

  • 7/27/2019 hasil spss asumsi.docx

    87/117

    Model Description

    Model Name MOD_35

    Dependent Variable 1 Kinerja berdasarkan Kualitas

    Equation 1 Linear

    Independent Variable Keselamatan Kerja

    Constant Included

    Variable Whose Values Label Observations in Plots Unspecified

    Case Processing Summary

    N

    Total Cases 112

    Excluded Casesa 0

    Forecasted Cases 0

    Newly Created Cases 0

    a. Cases with a missing value in any

    variable are excluded from the analysis.

    Variable Processing Summary

    Variables

    Dependent Independent

    Kinerja

    berdasarkan

    Kualitas Keselamatan Kerja

    Number of Positive Values 112 112

    Number of Zeros 0 0

    Number of Negative Values 0 0

    Number of Missing Values User-Missing 0 0

    System-Missing 0 0

    Model Summary and Parameter Estimates

    Dependent Variable:Kinerja berdasarkan Kualitas

    Equation

    Model Summary Parameter Estimates

    R Square F df1 df2 Sig. Constant b1

    Linear 001 059 1 110 809 22 475 - 022

  • 7/27/2019 hasil spss asumsi.docx

    88/117

    Linear .001 .059 1 110 .809 22.