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  • 7/30/2019 PRAKTIKUM JAWAB 20

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    PRAKTIKUM SPSS

    1. Buatlah Variabel IMT dan sajikan dalam bentuk frekuensi distribusi untuk data

    kualitatif:

    kategori imt

    Frequency Percent Valid Percent

    Cumulative

    Percent

    Valid underweight 40 30,1 30,1 30,1

    healthy weight 31 23,3 23,3 53,4

    overweight 17 12,8 12,8 66,2

    heavily overweight 27 20,3 20,3 86,5

    obese 18 13,5 13,5 100,0

    Total 133 100,0 100,0

    Kesimpulan:

    IMT terbanyak underweight dengan persentase 30,1% (n=40) dan IMT paling sedikit

    overweight 12,8% (n=17)

    2. Buatlah Frekuensi Distribusi umur penderita

    Banyak kelas interval = 1+3,3logn = 1+3,3log133 = 7,99 = 8

    Panjang kelas interval = nilai terbesar-nilai terkecil/banyak kelas = 80-22/8 = 58/8 =

    7,25Lebar kelas dipilih 10 untuk mempermudah pembagian.

    Jadi, frekuensi ditribusi umur penderita:

    22-31

    32-41

    42-51

    52-61

    62-71

    72-81

    3.Buatlah tabel frekuensi distribusi umur:

    kategori umur

    Frequency Percent Valid Percent

    Cumulative

    Percent

    Valid 22-31 10 7,5 7,5 7,5

    32-41 25 18,8 18,8 26,3

    42-51 36 27,1 27,1 53,4

    52-61 38 28,6 28,6 82,0

    62-71 17 12,8 12,8 94,7

    72-81 7 5,3 5,3 100,0

    Total 133 100,0 100,0

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    kategori umur * kategori GDS Crosstabulation

    Count

    kategori GDS

    TotalNormal tidak normal

    kategori umur 22-31 9 1 10

    32-41 22 3 25

    42-51 34 2 36

    52-61 32 6 38

    62-71 16 1 17

    72-81 7 0 7

    Total 120 13 133

    4. Ujilah apakah umur berdistribusi normal:

    Tests of Normality

    Kolmogorov-Smirnova Shapiro-Wilk

    Statistic df Sig. Statistic df Sig.

    Umur ,052 133 ,200* ,989 133 ,406

    a. Lilliefors Significance Correction

    *. This is a lower bound of the true significance.

    Kesimpulan: nilai Kolmogorov-Sminov dilihat dari nilai Sig. 0,200 > 0,05 = umur

    distribusi normal.

    5. Buatlah angka kejadian PJK berdasarkan frekuensi distribusi umur dan buatlah

    ulasannya:

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    kategori umur * PJK Crosstabulation

    PJK

    Total0 1

    kategori umur 22-31 Count 7 3 10

    Expected Count 7,1 2,9 10,0

    % within kategori umur 70,0% 30,0% 100,0%

    32-41 Count 18 7 25

    Expected Count 17,9 7,1 25,0

    % within kategori umur 72,0% 28,0% 100,0%

    42-51 Count 28 8 36

    Expected Count 25,7 10,3 36,0

    % within kategori umur 77,8% 22,2% 100,0%

    52-61 Count 26 12 38

    Expected Count 27,1 10,9 38,0

    % within kategori umur 68,4% 31,6% 100,0%

    62-71 Count 11 6 17

    Expected Count 12,1 4,9 17,0

    % within kategori umur 64,7% 35,3% 100,0%

    72-81 Count 5 2 7

    Expected Count 5,0 2,0 7,0

    % within kategori umur 71,4% 28,6% 100,0%

    Total Count 95 38 133

    Expected Count 95,0 38,0 133,0

    % within kategori umur 71,4% 28,6% 100,0%

    Kesimpulan:

    1. Angka kejadian PJK paling banyak pada kategori umur 52-61

    2. Angka kejadian PJK paling sedikit pada kategori umur 22-31

    6. Hitunglah korelasi umur dan tekanan darah sistolik, berapa nilai p dan buat

    interpretasinya:

    Correlations

    Umur Sistolik

    Umur Pearson Correlation 1 ,095

    Sig. (2-tailed) ,275

    N 133 133

    Sistolik Pearson Correlation ,095 1

    Sig. (2-tailed) ,275

    N 133 133

    Kesimpulan:

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    1. r hitung = 0,095 berada diantara 0-0,25 = korelasi sangat lemah

    2. p hitung = 0,275 > 0,05 = Ho gagal ditolak = tidak ada hubungan signifikan

    antara umur dan tekanan darah sistolik.

    7. Apakah ada perbedaan tekanan darah sistolik antar kelompok IMT:

    Multiple Comparisons

    Sistolik

    Bonferroni

    (I) kategori imt (J) kategori imt Mean Difference

    (I-J) Std. Error Sig.

    95% Confidence Interval

    Lower Bound Upper Bound

    underweight healthy weight -9,824 5,001 ,516 -24,11 4,46

    Overweight -13,285 6,051 ,299 -30,57 4,00

    heavily overweight -23,050* 5,205 ,000 -37,92 -8,18

    Obese -17,439* 5,931 ,039 -34,38 -,50

    healthy weight Underweight 9,824 5,001 ,516 -4,46 24,11

    Overweight -3,461 6,307 1,000 -21,48 14,56

    heavily overweight -13,226 5,501 ,176 -28,94 2,49

    Obese -7,615 6,193 1,000 -25,30 10,08

    overweight Underweight 13,285 6,051 ,299 -4,00 30,57

    healthy weight 3,461 6,307 1,000 -14,56 21,48

    heavily overweight -9,765 6,470 1,000 -28,25 8,72

    Obese -4,154 7,068 1,000 -24,34 16,04heavily overweight Underweight 23,050* 5,205 ,000 8,18 37,92

    healthy weight 13,226 5,501 ,176 -2,49 28,94

    Overweight 9,765 6,470 1,000 -8,72 28,25

    Obese 5,611 6,359 1,000 -12,55 23,78

    obese Underweight 17,439* 5,931 ,039 ,50 34,38

    healthy weight 7,615 6,193 1,000 -10,08 25,30

    Overweight 4,154 7,068 1,000 -16,04 24,34

    heavily overweight -5,611 6,359 1,000 -23,78 12,55

    *. The mean difference is significant at the 0.05 level.

    Kesimpulan:

    1. Nilai Sig.< 0,05 = bermakna perbedaannya

    Berarti kategori IMT yang bermakna perbedaannya :

    a. Underweight-heavily underweight

    b. Healthy weight-obese

    c. Heavily overweight-underweight

    d. Obese-underweight

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    8. Apakah variabel gula darah sewaktu berdistribusi normal:

    Tests of Normality

    Kolmogorov-Smirnova Shapiro-Wilk

    Statistic df Sig. Statistic df Sig.

    Gula Darah Sewaktu ,288 133 ,000 ,507 133 ,000

    a. Lilliefors Significance Correction

    Kesimpulan: nilai Sig. Kolmogorov-Sminov 0,0005 < 0,05 = variable gula darah

    sewaktu tidak berdistribusi normal.

    9. Bagilah LDL kolesterol menjadi 100 dengan membuat katLDL beri

    label 0 dan 1:

    kategori LDL

    Frequency Percent Valid Percent

    Cumulative

    Percent

    Valid normal 38 28,6 28,6 28,6

    tidak normal 95 71,4 71,4 100,0

    Total 133 100,0 100,0

    Kesimpulan: LDL tidak normal ada 95 (71,4%)

    10. Buktikan apakah ada hubungan antara LDL dan kejadian PJK:

    kategori LDL * PJK Crosstabulation

    PJK

    Total0 1

    kategori LDL normal Count 26 12 38

    Expected Count 27,1 10,9 38,0% within kategori LDL 68,4% 31,6% 100,0%

    tidak normal Count 69 26 95

    Expected Count 67,9 27,1 95,0

    % within kategori LDL 72,6% 27,4% 100,0%

    Total Count 95 38 133

    Expected Count 95,0 38,0 133,0

    % within kategori LDL 71,4% 28,6% 100,0%

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    Chi-Square Tests

    Value df

    Asymp. Sig. (2-

    sided)

    Exact Sig. (2-

    sided)

    Exact Sig. (1-

    sided)

    Pearson Chi-Square ,236a 1 ,627

    Continuity Correctionb ,075 1 ,785

    Likelihood Ratio ,233 1 ,629

    Fisher's Exact Test ,673 ,388

    Linear-by-Linear Association ,234 1 ,629

    N of Valid Cases 133

    a. 0 cells (,0%) have expected count less than 5. The minimum expected count is 10,86.

    b. Computed only for a 2x2 table

    Keterangan:

    1. Jika table 2x2 nilai expected pada table cross tabulation tidak ada 0,05 berarti Ho gagal ditolak

    4. Untuk memastikan lagi, lihat nilai value 0,075 < X2 tabel (3,841 pada 0,05)

    = Ho gagal ditolak/Ho diterima

    11. Dengan berpatokan GDS>200 mg% berapa angka kejadian DM:

    kategori GDS

    Frequency Percent Valid Percent

    Cumulative

    Percent

    Valid normal 120 90,2 90,2 90,2

    tidak normal 13 9,8 9,8 100,0

    Total 133 100,0 100,0

    Kesimpulan: 13 penderita DM

    12. Apakah ada hubungan DM dan kejadian PJK. Buatlah ulasannya:

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    Kategori GDS * PJK Crosstabulation

    PJK

    Total0 1

    kategori GDS normal Count 86 34 120

    Expected Count 85,7 34,3 120,0

    % within kategori GDS 71,7% 28,3% 100,0%

    tidak normal Count 9 4 13

    Expected Count 9,3 3,7 13,0

    % within kategori GDS 69,2% 30,8% 100,0%

    Total Count 95 38 133

    Expected Count 95,0 38,0 133,0

    % within kategori GDS 71,4% 28,6% 100,0%

    Chi-Square Tests

    Value df

    Asymp. Sig. (2-

    sided)

    Exact Sig. (2-

    sided)

    Exact Sig. (1-

    sided)

    Pearson Chi-Square ,034a 1 ,853

    Continuity Correctionb ,000 1 1,000

    Likelihood Ratio ,034 1 ,854

    Fisher's Exact Test 1,000 ,540

    Linear-by-Linear Association ,034 1 ,854

    N of Valid Cases 133

    a. 1 cells (25,0%) have expected count less than 5. The minimum expected count is 3,71.

    b. Computed only for a 2x2 table

    Kesimpulan: ada 1 sel yang nilai expected < 5, jadi dilihat nilai Sig. Fishers Exact

    Test = 1,000 > 0,05 berarti Ho gagal ditolak/Ho diterima = Tidak ada hubungan d dan

    PJK

    13. Apakah ada hubungan Genetik PJK dan angka kejadian PJK:

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    Genetik * PJK Crosstabulation

    PJK

    Total0 1

    Genetik Tidak ada genetik Count 95 14 109

    Expected Count 77,9 31,1 109,0

    % within Genetik 87,2% 12,8% 100,0%

    Ada Genetik Count 0 24 24

    Expected Count 17,1 6,9 24,0

    % within Genetik ,0% 100,0% 100,0%

    Total Count 95 38 133

    Expected Count 95,0 38,0 133,0

    % within Genetik 71,4% 28,6% 100,0%

    Chi-Square Tests

    Value Df

    Asymp. Sig. (2-

    sided)

    Exact Sig. (2-

    sided)

    Exact Sig. (1-

    sided)

    Pearson Chi-Square 73,211a 1 ,000

    Continuity Correctionb 69,003 1 ,000

    Likelihood Ratio 75,556 1 ,000

    Fisher's Exact Test ,000 ,000

    N of Valid Cases 133

    a. 0 cells (,0%) have expected count less than 5. The minimum expected count is 6,86.

    b. Computed only for a 2x2 table

    Kesimpulan:

    1. Nilai expected < 5, lihat nilai Asymp.Sig 0,0005 < 0,05 = Ho ditolak berarti ada

    hubungan Genetik dan PJK

    2. Memastikan lihat nilai value 69,003 > 3,841 (nilai chi square tabel) = Ho ditolak.

    14. Berapa angka kejadian Hipertensi:

    kategori sistolik

    Frequency Percent Valid Percent

    Cumulative

    Percent

    Valid normal 75 56,4 56,4 56,4

    hipertensi 58 43,6 43,6 100,0

    Total 133 100,0 100,0

    Kesimpulan: 58 orang penderita hipertensi (43,6%)

    15. Apakah ada hubungan hipertensi dengan kejadian PJK:

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    kategori sistolik * PJK Crosstabulation

    PJK

    Total0 1

    kategori sistolik normal Count 55 20 75

    Expected Count 53,6 21,4 75,0

    % within kategori sistolik 73,3% 26,7% 100,0%

    hipertensi Count 40 18 58

    Expected Count 41,4 16,6 58,0

    % within kategori sistolik 69,0% 31,0% 100,0%

    Total Count 95 38 133

    Expected Count 95,0 38,0 133,0

    % within kategori sistolik 71,4% 28,6% 100,0%

    Chi-Square Tests

    Value df

    Asymp. Sig. (2-

    sided)

    Exact Sig. (2-

    sided)

    Exact Sig. (1-

    sided)

    Pearson Chi-Square ,306a 1 ,580

    Continuity Correctionb ,129 1 ,719

    Likelihood Ratio ,305 1 ,581

    Fisher's Exact Test ,699 ,359

    Linear-by-Linear Association ,303 1 ,582N of Valid Cases 133

    a. 0 cells (,0%) have expected count less than 5. The minimum expected count is 16,57.

    b. Computed only for a 2x2 table

    Kesimpulan: 0,719 > 0,05 = Ho gagal ditolak = tidak ada hubungan Hipertensi dengan

    PJK

    16. Hitunglah korelasi antara hemotokrit dan total kolesterol:

    Correlations

    Hemotokrit

    kategori total

    kolesterol

    Hemotokrit Pearson Correlation 1 ,010

    Sig. (2-tailed) ,912

    N 133 133

    kategori total kolesterol Pearson Correlation ,010 1

    Sig. (2-tailed) ,912

    N 133 133

    Kesimpulan:

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    1. Nilai Sig. 0,975 > 0,05 = Ho diterima

    2. Nilai r (korelasi Pearson) 0,03 = berada diantara 0-0,25 = korelasi lemah

    17. Apakah ada perbedaan rerat tekanan darah antar kelompok LDL kolesterol:

    Independent Samples Test

    Levene's Test for Equality of

    Variances t-tes

    F Sig. t df Sig. (2-tailed) Mean

    Sisto

    lik

    Equal variances assumed 2,116 ,148 -1,862 131 ,065

    Equal variances not

    assumed

    -1,977 77,913 ,052

    Kesimpulan:

    1. Lihat Independent Sample Test pada Levenes Test for Equality of Variances

    Sig. 0,148 > 0,05 = Varian sama

    2. Jika Sig. < 0,05 = varian beda, lihat nilai Sig.2-tailed yang Equal variance not

    assumed.

    3. Lanjut dari nomor 1: lalu lihat Sig.2-tailed yang Equal Variance assumed

    0,065 > 0,05 = Ho diterima

    18. Apakah ada perbedaan rerata kadar kolesterol antar kelompok IMT:

    ANOVA

    Total Cholesterol

    Sum of Squares df Mean Square F Sig.

    Between Groups 17146,507 4 4286,627 1,463 ,217

    Within Groups 375159,463 128 2930,933

    Total 392305,970 132

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    Multiple Comparisons

    Total Cholesterol

    Bonferroni

    (I) kategori imt (J) kategori imt Mean Difference

    (I-J) Std. Error Sig.

    95% Confidence Interval

    Lower Bound Upper Bound

    Underweight healthy weight 1,167 13,076 1,000 -36,18 38,52

    Overweight 4,500 15,366 1,000 -39,39 48,39

    heavily overweight -23,870 13,484 ,791 -62,39 14,65

    Obese 11,000 15,366 1,000 -32,89 54,89

    healthy weight Underweight -1,167 13,076 1,000 -38,52 36,18

    Overweight 3,333 16,141 1,000 -42,77 49,44

    heavily overweight -25,037 14,361 ,837 -66,06 15,99

    Obese 9,833 16,141 1,000 -36,27 55,94

    Overweight Underweight -4,500 15,366 1,000 -48,39 39,39

    healthy weight -3,333 16,141 1,000 -49,44 42,77

    heavily overweight -28,370 16,474 ,875 -75,43 18,69

    Obese 6,500 18,046 1,000 -45,05 58,05

    heavily overweight Underweight 23,870 13,484 ,791 -14,65 62,39

    healthy weight 25,037 14,361 ,837 -15,99 66,06

    Overweight 28,370 16,474 ,875 -18,69 75,43

    Obese 34,870 16,474 ,362 -12,19 81,93

    Obese Underweight -11,000 15,366 1,000 -54,89 32,89

    healthy weight -9,833 16,141 1,000 -55,94 36,27

    Overweight -6,500 18,046 1,000 -58,05 45,05

    heavily overweight -34,870 16,474 ,362 -81,93 12,19

    Kesimpulan:

    1. Nilai Sig. 0,217 > 0,05 = Ho diterima

    2. Untuk lebih memastikan lihat nilai Sig. Tiap kelompok IMT > 0,05 = Ho

    diterima = tidak ada perbedaan rerata kadar total kolesterol antar kelompok

    IMT

    19. Apakah ada perbedaan rerata kadar gula darah antar kelompok IMT:

    ANOVA

    kategori GDS

    Sum of Squares df Mean Square F Sig.

    Between Groups ,099 4 ,025 ,272 ,896

    Within Groups 11,631 128 ,091

    Total 11,729 132

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    Multiple Comparisons

    kategori GDS

    Bonferroni

    (I) kategori imt (J) kategori imt Mean Difference

    (I-J) Std. Error Sig.

    95% Confidence Interval

    Lower Bound Upper Bound

    Underweight healthy weight -,058 ,073 1,000 -,27 ,15

    Overweight ,019 ,086 1,000 -,22 ,26

    heavily overweight -,036 ,075 1,000 -,25 ,18

    Obese -,036 ,086 1,000 -,28 ,21

    healthy weight Underweight ,058 ,073 1,000 -,15 ,27

    Overweight ,078 ,090 1,000 -,18 ,33

    heavily overweight ,022 ,080 1,000 -,21 ,25

    Obese ,022 ,090 1,000 -,23 ,28

    Overweight Underweight -,019 ,086 1,000 -,26 ,22

    healthy weight -,078 ,090 1,000 -,33 ,18

    heavily overweight -,056 ,092 1,000 -,32 ,21

    Obese -,056 ,100 1,000 -,34 ,23

    heavily overweight Underweight ,036 ,075 1,000 -,18 ,25

    healthy weight -,022 ,080 1,000 -,25 ,21

    Overweight ,056 ,092 1,000 -,21 ,32

    Obese ,000 ,092 1,000 -,26 ,26

    Obese Underweight ,036 ,086 1,000 -,21 ,28

    healthy weight -,022 ,090 1,000 -,28 ,23

    Overweight ,056 ,100 1,000 -,23 ,34

    heavily overweight ,000 ,092 1,000 -,26 ,26

    Kesimpulan:

    1. Nilai Sig. 0,896 > 0,05 = Ho diterima = tidak ada perbedaan rerata kadar gula

    darah antar kelompok IMT

    20. Hitunglah korelasi kadar gula darah dengan total kolesterol:

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    Correlations

    kategori total

    kolesterol

    Gula Darah

    Sewaktu

    kategori total kolesterol Pearson Correlation 1 ,211*

    Sig. (2-tailed) ,015

    N 133 133

    Gula Darah Sewaktu Pearson Correlation ,211* 1

    Sig. (2-tailed) ,015

    N 133 133

    *. Correlation is significant at the 0.05 level (2-tailed).

    Kesimpulan:

    1. Nilai Korelasi Pearson 0,211 = berada 0-0,25 = korelasi lemah