praktikum jawab 20
TRANSCRIPT
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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