standar nasional indonesia (sni 01-3710-1995)53 lampiran 1 standar nasional indonesia (sni...
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53
LAMPIRAN 1
Standar Nasional Indonesia (SNI 01-3710-1995)
Tabel Syarat Mutu Buah Kering
NO. KRITERIA UJI SATUAN PERSYARATAN 1. Keadaan :
1.1. Penampakan - Normal 1.2. Bau - Normal 1.3. Rasa - Normal 2. Air % b/b Maks. 31 3. Bahan tambahan makanan :
3.1. Pemanis buatan (sakarin, siklamat) - Negatif 3.2. Pewarna sesuai SNI 01-0222-1987 3.3. Pengawet sesuai SNI 01-0222-1987 4. Cemaran logam :
4.1. Timbal (Pb) mg/kg Maks. 2,0 4.2. Tembaga (Cu) mg/kg Maks. 5,0 4.3. Seng (Zn) mg/kg Maks. 40,0 4.4. Timah (Sn) mg/kg Maks. 40,0/251** 4.5. Raksa (Hg) mg/kg Maks. 0,03 5. Cemaran Arsen (As) mg/kg Maks. 1,0 6. Cemaran mikrobia :
6.1. E. coli APM/g < 3 ** Khusus untuk produk yang dikemas dalam kaleng
54
LAMPIRAN 2
LEMBAR KUISIONER
Dihadapan saudara terdapat 12 jenis manisan nanas. Saudara diminta memberi penilaian
berdasarkan tingkat kesukaan saudara dengan range nilai yang telah tersedia. Atas kerja
sama saudara, saya ucapkan terima kasih.
Kriteria 235 248 255 305 332 375 Warna Aroma Rasa
Tekstur Overall
Kriteria 418 422 455 536 542 599 Warna Aroma Rasa
Tekstur Overall
Range Nilai :
1 : Tidak Suka
2 : Agak Suka
3 : Suka
4 : Sangat Suka
5 : Sangat Suka Sekali
***GOD BLESS YOU***
55
LAMPIRAN 3
Nonlinear Regression Analysis [DataSet1] H:\laju pengeringan\laju 0 jam 1cm.sav
Iteration Historyb
21999.411 1.000 -.01018214.956 75.063 -3.14218214.956 75.063 -3.1426.0E+020 68.343 1.231
18166.411 71.499 -2.90718166.411 71.499 -2.90718020.748 69.050 -2.02918020.748 69.050 -2.029
6272.050 69.007 -.1926272.050 69.007 -.192
188962.55 64.739 .0964688.099 69.803 -.1604688.099 69.803 -.1602022.195 71.571 -.1122022.195 71.571 -.112
663.288 73.858 -.048663.288 73.858 -.048348.708 76.496 -.067348.708 76.496 -.067348.012 76.049 -.067348.012 76.049 -.067348.012 76.051 -.067348.012 76.051 -.067348.012 76.051 -.067
Iteration Numbera
1.01.12.02.12.23.03.14.04.15.05.15.26.06.17.07.18.08.19.09.110.010.111.011.1
ResidualSum of
Squares a bParameter
Derivatives are calculated numerically.Major iteration number is displayed to the left ofthe decimal, and minor iteration number is to theright of the decimal.
a.
Run stopped after 24 model evaluations and 11derivative evaluations because the relativereduction between successive residual sums ofsquares is at most SSCON = 1.00E-008.
b.
Parameter Estimates
76.051 5.194 63.768 88.334-.067 .010 -.091 -.042
Parameterab
Estimate Std. Error Lower Bound Upper Bound95% Confidence Interval
Correlations of Parameter Estimates
1.000 -.725-.725 1.000
ab
a b
ANOVAa
22440.535 2 11220.267348.012 7 49.716
22788.547 92914.126 8
SourceRegressionResidualUncorrected TotalCorrected Total
Sum ofSquares df
MeanSquares
Dependent variable: yR squared = 1 - (Residual Sum of Squares) /(Corrected Sum of Squares) = .881.
a.
56
Nonlinear Regression Analysis [DataSet2] H:\laju pengeringan\laju 0jam, 2cm.sav
Iteration History b
30218.395 1.000 -.01025236.307 83.422 -3.08225236.307 83.422 -3.0826.2E+019 77.811 .921
25189.113 80.090 -2.80425189.113 80.090 -2.80425003.387 78.382 -1.98925003.387 78.382 -1.98915828.937 78.531 -.33015828.937 78.531 -.3303.5E+011 66.273 .450
12908.356 79.010 -.25412908.356 79.010 -.2546708.188 80.130 -.1536708.188 80.130 -.153417.588 82.951 -.058417.588 82.951 -.058387.460 86.106 -.064387.460 86.106 -.064387.241 85.868 -.064387.241 85.868 -.064387.239 85.893 -.064387.239 85.893 -.064387.239 85.891 -.064387.239 85.891 -.064387.239 85.891 -.064
Iteration Number a
1.01.12.02.12.23.03.14.04.15.05.15.26.06.17.07.18.08.19.09.110.010.111.011.112.012.1
ResidualSum ofSquares a b
Parameter
Derivatives are calculated numerically.Major iteration number is displayed to the left ofthe decimal, and minor iteration number is to theright of the decimal.
a.
Run stopped after 26 model evaluations and 12derivative evaluations because the relativereduction between successive residual sums ofsquares is at most SSCON = 1.00E-008.
b.
Parameter Estimates
85.891 4.616 75.449 96.333-.064 .007 -.080 -.048
Parameterab
Estimate Std. Error Lower Bound Upper Bound95% Confidence Interval
Correlations of Parameter Estimates
1.000 -.719-.719 1.000
ab
a b
ANOVAa
30823.496 2 15411.748387.239 9 43.027
31210.735 114912.315 10
SourceRegressionResidualUncorrected TotalCorrected Total
Sum ofSquares df
MeanSquares
Dependent variable: yR squared = 1 - (Residual Sum of Squares) /(Corrected Sum of Squares) = .921.
a.
57
Nonlinear Regression Analysis [DataSet3] H:\laju pengeringan\laju 0jam, 3cm.sav
Iteration Historyb
30108.558 1.000 -.01024689.086 84.901 -3.26924689.086 84.901 -3.2692.3E+022 80.225 1.187
24651.099 81.792 -2.93824651.099 81.792 -2.93824467.274 80.599 -2.03424467.274 80.599 -2.034
9873.742 80.869 -.2119873.742 80.869 -.211
1468035.7 73.078 .1367596.282 81.623 -.1757596.282 81.623 -.1753512.680 83.287 -.1213512.680 83.287 -.121
426.590 86.134 -.055426.590 86.134 -.055286.370 87.343 -.065286.370 87.343 -.065286.228 87.101 -.065286.228 87.101 -.065286.228 87.106 -.065286.228 87.106 -.065286.228 87.105 -.065
Iteration Numbera
1.01.12.02.12.23.03.14.04.15.05.15.26.06.17.07.18.08.19.09.110.010.111.011.1
ResidualSum of
Squares a bParameter
Derivatives are calculated numerically.Major iteration number is displayed to the left ofthe decimal, and minor iteration number is to theright of the decimal.
a.
Run stopped after 24 model evaluations and 11derivative evaluations because the relativereduction between successive residual sums ofsquares is at most SSCON = 1.00E-008.
b.
Parameter Estimates
87.105 4.296 77.199 97.012-.065 .007 -.081 -.049
Parameterab
Estimate Std. Error Lower Bound Upper Bound95% Confidence Interval
Correlations of Parameter Estimates
1.000 -.723-.723 1.000
ab
a b
ANOVAa
30784.433 2 15392.217286.228 8 35.778
31070.661 104185.399 9
SourceRegressionResidualUncorrected TotalCorrected Total
Sum ofSquares df
MeanSquares
Dependent variable: yR squared = 1 - (Residual Sum of Squares) /(Corrected Sum of Squares) = .932.
a.
58
Nonlinear Regression Analysis [DataSet6] H:\laju pengeringan\laju 12jam, 1cm.sav
Iteration History b
22517.282 1.000 -.01018837.272 68.489 -2.14218837.272 68.489 -2.1421.6E+022 67.658 1.067
18728.859 68.242 -1.82118728.859 68.242 -1.82118110.538 68.239 -1.17818110.538 68.239 -1.1781287072.8 68.765 .12017842.382 68.315 -1.04817842.382 68.315 -1.04816942.253 68.474 -.77816942.253 68.474 -.7789713.219 68.756 -.2409713.219 68.756 -.240487.999 70.114 -.069487.999 70.114 -.069163.911 69.178 -.049163.911 69.178 -.049152.503 69.993 -.053152.503 69.993 -.053152.484 69.911 -.052152.484 69.911 -.052152.484 69.916 -.053152.484 69.916 -.053152.484 69.915 -.053
Iteration Number a
1.01.12.02.12.23.03.14.04.14.25.05.16.06.17.07.18.08.19.09.110.010.111.011.112.012.1
ResidualSum ofSquares a b
Parameter
Derivatives are calculated numerically.Major iteration number is displayed to the left ofthe decimal, and minor iteration number is to theright of the decimal.
a.
Run stopped after 26 model evaluations and 12derivative evaluations because the relativereduction between successive residual sums ofsquares is at most SSCON = 1.00E-008.
b.
Parameter Estimates
69.915 2.805 63.571 76.260-.053 .005 -.063 -.042
Parameterab
Estimate Std. Error Lower Bound Upper Bound95% Confidence Interval
Correlations of Parameter Estimates
1.000 -.740-.740 1.000
ab
a b
ANOVAa
23242.993 2 11621.497152.484 9 16.943
23395.478 112547.655 10
SourceRegressionResidualUncorrected TotalCorrected Total
Sum ofSquares df
MeanSquares
Dependent variable: yR squared = 1 - (Residual Sum of Squares) /(Corrected Sum of Squares) = .940.
a.
59
Nonlinear Regression Analysis [DataSet7] H:\laju pengeringan\laju 12jam, 2cm.sav
Iteration History b
27390.169 1.000 -.01023633.375 70.557 -1.80623633.375 70.557 -1.8062.5E+026 69.317 1.189
23424.862 70.322 -1.50623424.862 70.322 -1.50622272.367 70.311 -.90622272.367 70.311 -.9068.3E+010 70.686 .372
21774.259 70.383 -.78621774.259 70.383 -.78620092.883 70.523 -.54620092.883 70.523 -.54613738.928 70.883 -.24113738.928 70.883 -.241
1878.123 72.074 -.0751878.123 72.074 -.075
547.042 68.676 -.030547.042 68.676 -.030201.718 71.545 -.043201.718 71.545 -.043201.078 71.371 -.043201.078 71.371 -.043201.078 71.361 -.043201.078 71.361 -.043201.078 71.362 -.043201.078 71.362 -.043201.078 71.362 -.043
Iteration Number a
1.01.12.02.12.23.03.14.04.14.25.05.16.06.17.07.18.08.19.09.110.010.111.011.112.012.113.013.1
ResidualSum of
Squares a bParameter
Derivatives are calculated numerically.Major iteration number is displayed to the left ofthe decimal, and minor iteration number is to theright of the decimal.
a.
Run stopped after 28 model evaluations and 13derivative evaluations because the relativereduction between successive residual sums ofsquares is at most SSCON = 1.00E-008.
b.
Parameter Estimates
71.362 2.903 64.892 77.831-.043 .004 -.052 -.033
Parameterab
Estimate Std. Error Lower Bound Upper Bound95% Confidence Interval
Correlations of Parameter Estimates
1.000 -.754-.754 1.000
ab
a b
ANOVAa
28200.384 2 14100.192201.078 10 20.108
28401.461 122585.426 11
SourceRegressionResidualUncorrected TotalCorrected Total
Sum ofSquares df
MeanSquares
Dependent variable: yR squared = 1 - (Residual Sum of Squares) /(Corrected Sum of Squares) = .922.
a.
60
Nonlinear Regression Analysis [DataSet8] H:\laju pengeringan\laju 12jam, 3cm.sav
Iteration Historyb
18940.619 1.000 -.01014858.121 66.950 -2.52914858.121 66.950 -2.5296.2E+018 69.296 .966
14795.346 68.007 -2.17914795.346 68.007 -2.17914398.363 68.827 -1.45014398.363 68.827 -1.45026282.495 69.701 .02214216.542 68.940 -1.30214216.542 68.940 -1.30213615.169 69.149 -1.00613615.169 69.149 -1.0069466.244 69.520 -.3979466.244 69.520 -.3974848.430 70.747 -.0184848.430 70.747 -.018359.286 67.906 -.051359.286 67.906 -.051139.274 70.456 -.067139.274 70.456 -.067137.307 70.870 -.069137.307 70.870 -.069137.305 70.889 -.069137.305 70.889 -.069137.305 70.889 -.069
Iteration Number a
1.01.12.02.12.23.03.14.04.14.25.05.16.06.17.07.18.08.19.09.110.010.111.011.112.012.1
ResidualSum ofSquares a b
Parameter
Derivatives are calculated numerically.Major iteration number is displayed to the left ofthe decimal, and minor iteration number is to theright of the decimal.
a.
Run stopped after 26 model evaluations and 12derivative evaluations because the relativereduction between successive residual sums ofsquares is at most SSCON = 1.00E-008.
b.
Parameter Estimates
70.889 3.006 63.958 77.820-.069 .006 -.083 -.055
Parameterab
Estimate Std. Error Lower Bound Upper Bound95% Confidence Interval
Correlations of Parameter Estimates
1.000 -.716-.716 1.000
ab
a b
ANOVAa
19567.388 2 9783.694137.305 8 17.163
19704.693 102647.793 9
SourceRegressionResidualUncorrected TotalCorrected Total
Sum ofSquares df
MeanSquares
Dependent variable: yR squared = 1 - (Residual Sum of Squares) /(Corrected Sum of Squares) = .948.
a.
61
Nonlinear Regression Analysis [DataSet10] H:\laju pengeringan\laju 24jam, 1cm.sav
Iteration Historyb
18159,483 1,000 -,01014525,418 68,882 -2,85414525,418 68,882 -2,8541.9E+023 66,113 1,614
14478,387 67,357 -2,40714478,387 67,357 -2,40714066,601 66,771 -1,43614066,601 66,771 -1,4369.8E+009 67,148 ,516
13828,828 66,829 -1,24013828,828 66,829 -1,24012871,193 66,956 -,84412871,193 66,956 -,8445124,926 67,251 -,2125124,926 67,251 -,212212,731 69,335 -,072212,731 69,335 -,072161,364 69,482 -,063161,364 69,482 -,063160,903 69,733 -,064160,903 69,733 -,064160,901 69,707 -,064160,901 69,707 -,064160,901 69,709 -,064160,901 69,709 -,064160,901 69,708 -,064
Iteration Number a
1.01.12.02.12.23.03.14.04.14.25.05.16.06.17.07.18.08.19.09.110.010.111.011.112.012.1
ResidualSum ofSquares a b
Parameter
Derivatives are calculated numerically.Major iteration number is displayed to the left ofthe decimal, and minor iteration number is to theright of the decimal.
a.
Run stopped after 26 model evaluations and 12derivative evaluations because the relativereduction between successive residual sums ofsquares is at most SSCON = 1,00E-008.
b.
Parameter Estimates
69,708 3,888 60,195 79,222-,064 ,009 -,087 -,042
Parameterab
Estimate Std. Error Lower Bound Upper Bound95% Confidence Interval
Correlations of Parameter Estimates
1,000 -,734-,734 1,000
ab
a b
ANOVAa
18692,337 2 9346,169160,901 6 26,817
18853,238 81728,711 7
SourceRegressionResidualUncorrected TotalCorrected Total
Sum ofSquares df
MeanSquares
Dependent variable: yR squared = 1 - (Residual Sum of Squares) /(Corrected Sum of Squares) = ,907.
a.
62
Nonlinear Regression Analysis [DataSet11] H:\laju pengeringan\laju 24jam, 2cm.sav
Iteration Historyb
21940,283 1,000 -,01017971,826 70,313 -2,48717971,826 70,313 -2,4874.2E+018 69,535 ,859
17911,439 69,966 -2,15217911,439 69,966 -2,15217557,407 69,919 -1,48017557,407 69,919 -1,480
3537,602 70,461 -,1343537,602 70,461 -,1346817,080 67,479 -,008
268,994 72,679 -,072268,994 72,679 -,072137,437 72,670 -,061137,437 72,670 -,061135,582 73,038 -,062135,582 73,038 -,062135,579 73,006 -,062135,579 73,006 -,062135,579 73,008 -,062135,579 73,008 -,062135,579 73,008 -,062
Iteration Numbera
1.01.12.02.12.23.03.14.04.15.05.15.26.06.17.07.18.08.19.09.110.010.1
ResidualSum ofSquares a b
Parameter
Derivatives are calculated numerically.Major iteration number is displayed to the left ofthe decimal, and minor iteration number is to theright of the decimal.
a.
Run stopped after 22 model evaluations and 10derivative evaluations because the relativereduction between successive residual sums ofsquares is at most SSCON = 1,00E-008.
b.
Parameter Estimates
73,008 2,719 66,856 79,159-,062 ,005 -,073 -,051
Parameterab
Estimate Std. Error Lower Bound Upper Bound95% Confidence Interval
Correlations of Parameter Estimates
1,000 -,722-,722 1,000
ab
a b
ANOVAa
22658,421 2 11329,210135,579 9 15,064
22794,000 113213,199 10
SourceRegressionResidualUncorrected TotalCorrected Total
Sum ofSquares df
MeanSquares
Dependent variable: yR squared = 1 - (Residual Sum of Squares) /(Corrected Sum of Squares) = ,958.
a.
63
Nonlinear Regression Analysis [DataSet12] H:\laju pengeringan\laju 24jam, 3cm.sav
Iteration Historyb
21804,135 1,000 -,01017643,715 68,295 -2,26717643,715 68,295 -2,2673.0E+017 70,521 ,719
17559,017 69,151 -1,96817559,017 69,151 -1,96817106,457 69,975 -1,35417106,457 69,975 -1,3542305,325 70,968 -,1152305,325 70,968 -,1151249,181 70,037 -,0361249,181 70,037 -,036
67,900 71,595 -,05767,900 71,595 -,05741,756 72,601 -,06241,756 72,601 -,06241,732 72,639 -,06341,732 72,639 -,06341,732 72,639 -,063
Iteration Numbera
1.01.12.02.12.23.03.14.04.15.05.16.06.17.07.18.08.19.09.1
ResidualSum of
Squares a bParameter
Derivatives are calculated numerically.Major iteration number is displayed to the left ofthe decimal, and minor iteration number is to theright of the decimal.
a.
Run stopped after 19 model evaluations and 9derivative evaluations because the relativereduction between successive residual sums ofsquares is at most SSCON = 1,00E-008.
b.
Parameter Estimates
72,639 1,411 69,495 75,783-,063 ,002 -,068 -,057
Parameterab
Estimate Std. Error Lower Bound Upper Bound95% Confidence Interval
Correlations of Parameter Estimates
1,000 -,715-,715 1,000
ab
a b
ANOVAa
22639,633 2 11319,81741,732 10 4,173
22681,365 123474,965 11
SourceRegressionResidualUncorrected TotalCorrected Total
Sum ofSquares df
MeanSquares
Dependent variable: yR squared = 1 - (Residual Sum of Squares) /(Corrected Sum of Squares) = ,988.
a.
64
Nonlinear Regression Analysis [DataSet1] C:\DONNA\laju pengeringan\laju 72jam,1cm.sav
Iteration Historyb
13851,852 1,000 -,01010441,379 62,956 -2,99710441,379 62,956 -2,9973.7E+017 63,287 1,148
10418,001 63,169 -2,58210418,001 63,169 -2,58210239,904 63,352 -1,75110239,904 63,352 -1,751
134,224 63,819 -,089134,224 63,819 -,089
71,283 64,974 -,07871,283 64,974 -,07870,901 65,120 -,07970,901 65,120 -,07970,901 65,109 -,07970,901 65,109 -,07970,901 65,110 -,079
Iteration Numbera
1.01.12.02.12.23.03.14.04.15.05.16.06.17.07.18.08.1
ResidualSum of
Squares a bParameter
Derivatives are calculated numerically.Major iteration number is displayed to the left ofthe decimal, and minor iteration number is to theright of the decimal.
a.
Run stopped after 17 model evaluations and 8derivative evaluations because the relativereduction between successive residual sums ofsquares is at most SSCON = 1,00E-008.
b.
Parameter Estimates
65,110 2,654 58,616 71,603-,079 ,007 -,097 -,061
Parameterab
Estimate Std. Error Lower Bound Upper Bound95% Confidence Interval
Correlations of Parameter Estimates
1,000 -,711-,711 1,000
ab
a b
ANOVAa
14378,822 2 7189,41170,901 6 11,817
14449,723 81755,902 7
SourceRegressionResidualUncorrected TotalCorrected Total
Sum ofSquares df
MeanSquares
Dependent variable: yR squared = 1 - (Residual Sum of Squares) /(Corrected Sum of Squares) = ,960.
a.
65
Nonlinear Regression Analysis [DataSet14] H:\laju pengeringan\laju 72jam, 2cm.sav
Iteration Historyb
17742,542 1,000 -,01014103,251 68,250 -2,83714103,251 68,250 -2,8379.7E+022 66,030 1,591
14057,577 67,052 -2,39514057,577 67,052 -2,39513667,118 66,615 -1,46013667,118 66,615 -1,4606.4E+008 67,008 ,417
13450,272 66,673 -1,27213450,272 66,673 -1,27212613,195 66,798 -,89212613,195 66,798 -,892
4954,956 67,063 -,2154954,956 67,063 -,215
211,225 69,109 -,078211,225 69,109 -,078101,569 68,990 -,063101,569 68,990 -,063100,033 69,360 -,065100,033 69,360 -,065100,029 69,324 -,065100,029 69,324 -,065100,029 69,326 -,065100,029 69,326 -,065100,029 69,326 -,065
Iteration Numbera
1.01.12.02.12.23.03.14.04.14.25.05.16.06.17.07.18.08.19.09.110.010.111.011.112.012.1
ResidualSum of
Squares a bParameter
Derivatives are calculated numerically.Major iteration number is displayed to the left ofthe decimal, and minor iteration number is to theright of the decimal.
a.
Run stopped after 26 model evaluations and 12derivative evaluations because the relativereduction between successive residual sums ofsquares is at most SSCON = 1,00E-008.
b.
Parameter Estimates
69,326 3,071 61,811 76,841-,065 ,007 -,083 -,047
Parameterab
Estimate Std. Error Lower Bound Upper Bound95% Confidence Interval
Correlations of Parameter Estimates
1,000 -,733-,733 1,000
ab
a b
ANOVAa
18328,971 2 9164,485100,029 6 16,672
18429,000 81660,701 7
SourceRegressionResidualUncorrected TotalCorrected Total
Sum ofSquares df
MeanSquares
Dependent variable: yR squared = 1 - (Residual Sum of Squares) /(Corrected Sum of Squares) = ,940.
a.
66
Nonlinear Regression Analysis [DataSet3] C:\DONNA\laju pengeringan\laju 72jam, 3cm.sav
Iteration History b
20903,052 1,000 -,01017331,811 70,433 -2,58117331,811 70,433 -2,5817.8E+023 66,655 1,457
17266,959 68,838 -2,21717266,959 68,838 -2,21716840,652 67,912 -1,40916840,652 67,912 -1,4099390421.1 68,101 ,22316628,817 67,950 -1,24616628,817 67,950 -1,24615867,910 68,047 -,91515867,910 68,047 -,9158471,377 68,262 -,2538471,377 68,262 -,253557,920 69,855 -,077557,920 69,855 -,077191,954 70,377 -,053191,954 70,377 -,053176,436 71,346 -,058176,436 71,346 -,058176,395 71,214 -,058176,395 71,214 -,058176,394 71,223 -,058176,394 71,223 -,058176,394 71,222 -,058176,394 71,222 -,058176,394 71,223 -,058
Iteration Number a
1.01.12.02.12.23.03.14.04.14.25.05.16.06.17.07.18.08.19.09.110.010.111.011.112.012.113.013.1
ResidualSum ofSquares a b
Parameter
Derivatives are calculated numerically.Major iteration number is displayed to the left ofthe decimal, and minor iteration number is to theright of the decimal.
a.
Run stopped after 28 model evaluations and 13derivative evaluations because the relativereduction between successive residual sums ofsquares is at most SSCON = 1,00E-008.
b.
Parameter Estimates
71,223 3,623 62,654 79,791-,058 ,007 -,075 -,040
Parameterab
Estimate Std. Error Lower Bound Upper Bound95% Confidence Interval
Correlations of Parameter Estimates
1,000 -,740-,740 1,000
ab
a b
ANOVAa
21509,035 2 10754,517176,394 7 25,199
21685,429 92035,931 8
SourceRegressionResidualUncorrected TotalCorrected Total
Sum ofSquares df
MeanSquares
Dependent variable: yR squared = 1 - (Residual Sum of Squares) /(Corrected Sum of Squares) = ,913.
a.
67
LAMPIRAN 4
Uji Normalitas Manisan Nanas Kering
Tests of Normality
,173 9 ,200* ,949 9 ,677,166 9 ,200* ,964 9 ,843,196 9 ,200* ,902 9 ,263,149 9 ,200* ,960 9 ,803,208 9 ,200* ,878 9 ,151,209 9 ,200* ,853 9 ,081,175 9 ,200* ,911 9 ,320,212 9 ,200* ,884 9 ,174,300 9 ,019 ,846 9 ,067,259 9 ,083 ,845 9 ,065,222 9 ,200* ,838 9 ,055,191 9 ,200* ,917 9 ,365,147 9 ,200* ,983 9 ,979,152 9 ,200* ,948 9 ,664,179 9 ,200* ,926 9 ,441,150 9 ,200* ,937 9 ,549,188 9 ,200* ,895 9 ,224,184 9 ,200* ,895 9 ,224,227 9 ,199 ,905 9 ,285,223 9 ,200* ,910 9 ,318,275 9 ,049 ,837 9 ,054,184 9 ,200* ,901 9 ,260,182 9 ,200* ,898 9 ,238,190 9 ,200* ,894 9 ,218
Perendaman0 jam12 jam24 jam72 jam0 jam12 jam24 jam72 jam0 jam12 jam24 jam72 jam0 jam12 jam24 jam72 jam0 jam12 jam24 jam72 jam0 jam12 jam24 jam72 jam
Kadar_Air
Kadar_Abu
Vitamin_C
Kadar_Sukrosa
Hardness
Chewiness
Statistic df Sig. Statistic df Sig.Kolmogorov-Smirnova Shapiro-Wilk
This is a lower bound of the true significance.*.
Lilliefors Significance Correctiona.
Tests of Normality
,144 12 ,200* ,971 12 ,925,248 12 ,041 ,885 12 ,102,119 12 ,200* ,962 12 ,815,219 12 ,115 ,881 12 ,090,232 12 ,075 ,837 12 ,025,239 12 ,057 ,825 12 ,018,233 12 ,072 ,887 12 ,109,201 12 ,193 ,905 12 ,181,221 12 ,109 ,901 12 ,164,112 12 ,200* ,983 12 ,992,144 12 ,200* ,969 12 ,897,176 12 ,200* ,945 12 ,562,245 12 ,045 ,881 12 ,090,187 12 ,200* ,939 12 ,484,236 12 ,063 ,805 12 ,011,242 12 ,051 ,723 12 ,001,186 12 ,200* ,892 12 ,126,208 12 ,159 ,873 12 ,071
Ketebalan1 cm2 cm3 cm1 cm2 cm3 cm1 cm2 cm3 cm1 cm2 cm3 cm1 cm2 cm3 cm1 cm2 cm3 cm
Kadar_Air
Kadar_Abu
Vitamin_C
Kadar_Sukrosa
Hardness
Chewiness
Statistic df Sig. Statistic df Sig.Kolmogorov-Smirnova Shapiro-Wilk
This is a lower bound of the true significance.*.
Lilliefors Significance Correctiona.
68
LAMPIRAN 5
Uji Diskriptif Two Way
* Kadar Air Manisan Nanas Kering
Descriptive Statistics
Dependent Variable: Kadar_Air
19.4767 .37608 319.9533 .44298 320.1933 .38175 319.8744 .46974 920.1467 .44298 320.1967 .87460 320.2933 1.01894 320.2122 .70994 920.2400 .68242 320.4833 .90473 320.7300 1.02825 320.4844 .79398 920.6300 .38743 320.7733 .14503 320.9200 .44000 320.7744 .32704 920.1233 .60106 1220.3517 .65609 1220.5342 .73571 1220.3364 .66932 36
Ketebalan1 cm2 cm3 cmTotal1 cm2 cm3 cmTotal1 cm2 cm3 cmTotal1 cm2 cm3 cmTotal1 cm2 cm3 cmTotal
Perendaman0 jam
12 jam
24 jam
72 jam
Total
Mean Std. Deviation N
* Kadar Abu Manisan Nanas Kering
Descriptive Statistics
Dependent Variable: Kadar_Abu
5.5000 .20000 34.7667 .41633 33.2000 .17321 34.4889 1.04695 93.4000 .10000 31.7667 .28868 3
.9333 .11547 32.0333 1.09886 92.8667 .11547 32.4000 .17321 31.7000 .10000 32.3222 .52148 91.8000 .10000 31.2000 .17321 31.2667 .05774 31.4222 .30322 93.3917 1.41129 122.5333 1.43801 121.7750 .91067 122.5667 1.40895 36
Ketebalan1 cm2 cm3 cmTotal1 cm2 cm3 cmTotal1 cm2 cm3 cmTotal1 cm2 cm3 cmTotal1 cm2 cm3 cmTotal
Perendaman0 jam
12 jam
24 jam
72 jam
Total
Mean Std. Deviation N
69
* Kadar Vitamin C Manisan Nanas Kering
Descriptive Statistics
Dependent Variable: Vitamin_C
22.9567 1.01614 321.7833 2.03227 324.4233 .50807 323.0544 1.63321 917.6700 1.02191 317.6700 1.02191 321.1967 1.01614 318.8456 1.97221 915.9067 1.01614 318.2600 1.02191 316.4933 1.01614 316.8867 1.37941 914.1467 1.01614 315.9067 1.01614 317.6700 1.02191 315.9078 1.76209 917.6700 3.55093 1218.4050 2.50727 1219.9458 3.34216 1218.6736 3.22090 36
Ketebalan1 cm2 cm3 cmTotal1 cm2 cm3 cmTotal1 cm2 cm3 cmTotal1 cm2 cm3 cmTotal1 cm2 cm3 cmTotal
Perendaman0 jam
12 jam
24 jam
72 jam
Total
Mean Std. Deviation N
* Kadar Sukrosa Manisan Nanas Kering
Descriptive Statistics
Dependent Variable: Kadar_Sukrosa
79.7867 19.12820 368.4900 8.52741 344.2133 14.66490 364.1633 20.27856 998.3667 22.02644 393.9500 24.34611 390.6533 6.77809 394.3233 17.09368 989.3567 10.30756 367.1933 21.34690 375.1767 13.35552 377.2422 16.72061 985.6933 11.64546 356.4200 21.71946 343.6433 7.72118 361.9189 22.69997 988.3008 15.75669 1271.5133 22.28493 1263.4217 23.19411 1274.4119 22.66307 36
Ketebalan1 cm2 cm3 cmTotal1 cm2 cm3 cmTotal1 cm2 cm3 cmTotal1 cm2 cm3 cmTotal1 cm2 cm3 cmTotal
Perendaman0 jam
12 jam
24 jam
72 jam
Total
Mean Std. Deviation N
70
* Hardness Manisan Nanas Kering
Descriptive Statistics
Dependent Variable: Hardness
3.8708 1.96574 39.0035 2.68193 39.5499 2.87233 37.4747 3.49123 91.2043 .93636 34.0036 2.08254 34.2510 .50785 33.1530 1.87495 92.7789 2.43510 34.8486 1.35807 33.8974 1.46955 33.8416 1.81339 91.7175 .41976 34.5121 2.07393 33.4062 1.03795 33.2119 1.69538 92.3929 1.76584 125.5920 2.74675 125.2761 2.97918 124.4203 2.87606 36
Ketebalan1 cm2 cm3 cmTotal1 cm2 cm3 cmTotal1 cm2 cm3 cmTotal1 cm2 cm3 cmTotal1 cm2 cm3 cmTotal
Perendaman0 jam
12 jam
24 jam
72 jam
Total
Mean Std. Deviation N
* Chewiness Manisan Nanas Kering
Descriptive Statistics
Dependent Variable: Chewiness
.9213 .46163 31.9107 2.00819 32.3183 1.17230 31.7168 1.33869 9
.3234 .54201 3
.3037 .39084 3
.7143 .40126 3
.4471 .43832 91.5182 1.86891 31.4887 1.25500 3
.7415 .88941 31.2494 1.26888 9
.2283 .14703 31.5308 .72642 3
.7753 .66789 3
.8448 .75477 9
.7478 1.01191 121.3085 1.24094 121.1373 1.00585 121.0645 1.08645 36
Ketebalan1 cm2 cm3 cmTotal1 cm2 cm3 cmTotal1 cm2 cm3 cmTotal1 cm2 cm3 cmTotal1 cm2 cm3 cmTotal
Perendaman0 jam
12 jam
24 jam
72 jam
Total
Mean Std. Deviation N
71
LAMPIRAN 6
Uji Post Hoc Two Way Anova : * Kadar Air Manisan Nanas Kering
Kadar_Air
Duncana,b
9 19.87449 20.2122 20.21229 20.4844 20.48449 20.7744
.074 .098
Perendaman0 jam12 jam24 jam72 jamSig.
N 1 2Subset
Means for groups in homogeneous subsets are displayed.Based on Type III Sum of SquaresThe error term is Mean Square(Error) = .432.
Uses Harmonic Mean Sample Size = 9.000.a.
Alpha = .05.b.
Kadar_Air
Duncana,b
12 20.123312 20.351712 20.5342
.160
Ketebalan1 cm2 cm3 cmSig.
N 1Subset
Means for groups in homogeneous subsets are displayed.Based on Type III Sum of SquaresThe error term is Mean Square(Error) = .432.
Uses Harmonic Mean Sample Size = 12.000.a.
Alpha = .05.b.
* Kadar Abu Manisan Nanas Kering
72
Kadar_Abu
Duncana,b
9 1.42229 2.03339 2.32229 4.4889
1.000 1.000 1.000 1.000
Perendaman72 jam12 jam24 jam0 jamSig.
N 1 2 3 4Subset
Means for groups in homogeneous subsets are displayed.Based on Type III Sum of SquaresThe error term is Mean Square(Error) = .037.
Uses Harmonic Mean Sample Size = 9.000.a.
Alpha = .05.b.
* Kadar Vitamin C Manisan Nanas Kering
Vitamin_C
Duncana,b
9 15.90789 16.88679 18.84569 23.0544
.073 1.000 1.000
Perendaman72 jam24 jam12 jam0 jamSig.
N 1 2 3Subset
Means for groups in homogeneous subsets are displayed.Based on Type III Sum of SquaresThe error term is Mean Square(Error) = 1.230.
Uses Harmonic Mean Sample Size = 9.000.a.
Alpha = .05.b.
Vitamin_C
Duncana,b
12 17.670012 18.405012 19.9458
.118 1.000
Ketebalan1 cm2 cm3 cmSig.
N 1 2Subset
Means for groups in homogeneous subsets are displayed.Based on Type III Sum of SquaresThe error term is Mean Square(Error) = 1.230.
Uses Harmonic Mean Sample Size = 12.000.a.
Alpha = .05.b.
* Kadar Sukrosa Manisan Nanas Kering
73
Kadar_Sukrosa
Duncana,b
9 61.91899 64.16339 77.24229 94.3233
.070 1.000
Perendaman72 jam0 jam24 jam12 jamSig.
N 1 2Subset
Means for groups in homogeneous subsets are displayed.Based on Type III Sum of SquaresThe error term is Mean Square(Error) = 265.398.
Uses Harmonic Mean Sample Size = 9.000.a.
Alpha = .05.b.
Kadar_Sukrosa
Duncana,b
12 63.421712 71.513312 88.3008
.236 1.000
Ketebalan3 cm2 cm1 cmSig.
N 1 2Subset
Means for groups in homogeneous subsets are displayed.Based on Type III Sum of SquaresThe error term is Mean Square(Error) = 265.398.
Uses Harmonic Mean Sample Size = 12.000.a.
Alpha = .05.b.
* Hardness Manisan Nanas Kering
Hardness
Duncana,b
9 3.15309 3.21199 3.84169 7.4747
.460 1.000
Perendaman12 jam72 jam24 jam0 jamSig.
N 1 2Subset
Means for groups in homogeneous subsets are displayed.Based on Type III Sum of SquaresThe error term is Mean Square(Error) = 3.356.
Uses Harmonic Mean Sample Size = 9.000.a.
Alpha = .05.b.
74
Hardness
Duncana,b
12 2.392912 5.276112 5.5920
1.000 .677
Ketebalan1 cm3 cm2 cmSig.
N 1 2Subset
Means for groups in homogeneous subsets are displayed.Based on Type III Sum of SquaresThe error term is Mean Square(Error) = 3.356.
Uses Harmonic Mean Sample Size = 12.000.a.
Alpha = .05.b.
• Chewiness Manisan Nanas Kering
Chewiness
Duncana,b
9 .44719 .8448 .84489 1.2494 1.24949 1.7168
.136 .106
Perendaman12 jam72 jam24 jam0 jamSig.
N 1 2Subset
Means for groups in homogeneous subsets are displayed.Based on Type III Sum of SquaresThe error term is Mean Square(Error) = 1.090.
Uses Harmonic Mean Sample Size = 9.000.a.
Alpha = .05.b.
75
Chewiness
Duncana,b
12 .747812 1.137312 1.3085
.226
Ketebalan1 cm3 cm2 cmSig.
N 1Subset
Means for groups in homogeneous subsets are displayed.Based on Type III Sum of SquaresThe error term is Mean Square(Error) = 1.090.
Uses Harmonic Mean Sample Size = 12.000.a.
Alpha = .05.b.
76
LAMPIRAN 7
Berikut adalah waktu, suhu dalam dan suhu luar STD juga RH di dalam STD yang
dicatat dari pengukuran dengan alat thermohigrometer selama penimbangan sampel
guna menentukan laju pengeringan manisan nanas.
Pengambilan Ke- Waktu Pengambilan Suhu Dalam STD Suhu Luar STD RH 0 pukul 14.45 WIB 28.4 ºC 25.6 ºC 68 % 2 pukul 09.15 WIB 30 ºC 29.5 ºC 71 % 4 pukul 11.15 WIB 51.5 ºC 29.2 ºC 60 % 6 pukul 09.15 WIB 38.4 ºC 25.7 ºC 75 % 8 pukul 11.15 WIB 47.8 ºC 28 ºC 64 %
10 pukul 13.15 WIB 66.4 ºC 30.4 ºC 54 % 12 pukul 09.30 WIB 31 ºC 29.2 ºC 66 % 14 pukul 11.30 WIB 63 ºC 31.5 ºC 53 % 16 pukul 12.00 WIB 65.4 ºC 31.2 ºC 58 % 18 pukul 10.15 WIB 59.1 ºC 29.4 ºC 57 % 20 pukul 12.15 WIB 85 ºC 32 ºC 45 % 22 pukul 14.15 WIB 110 ºC 33.2 ºC 55 %