Pengaruh Faktor Lingkungan Dan Perilaku Terhadap Kejadian Malaria Di Kecamatan Siabu Kabupaten Mandailing Natal Tahun 2015

Teks penuh

(1)

145

TAHUN 2015

No. Rumah

:

Desa

:

Tanggal Wawancara :

A.

IDENTITAS RESPONDEN

a.

Nama

:

b.

Umur

:

c.

Jenis Kelamin : 1. Laki-laki 2. Wanita

d.

Pekerjaan

: 1. Petani

2. Nelayan

3. Pedagang

4. Pegawai Swasta

5. PNS/TNI/POLRI

e.

Apakah Bapak / Ibu pernah mengalami penyakit malaria dengan gejala :

demam, panas, mengigil, berkeringat dalam waktu 6 bulan terakhir…?

Jawaban

: 1. Pernah

2. Tidak pernah

B.

PENGETAHUAN

Petunjuk :

Jawablah pertanyaan dibawah ini menurut Anda paling benar dengan cara memberi

contreng / checklist

1.

Menurut Anda apakah penyakit malaria itu?

a.

Penyakit yang disebabkan oleh nyamuk (1)

b.

Penyakit yang disebabkan oleh virus dengue (0)

(2)

2.

Menurut anda, bagaimana cara penularan penyakit malaria?

a.

Melalui gigitan nyamuk (1)

b.

Melalui gigitan nyamuk anopheles (2)

c.

Melalui makanan (0)

3.

Pada umumnya penyakit malaria ditularkan ke manusia melalui gigitan?

a.

Nyamuk Anopheles (2)

b.

Nyamuk Aedes Aegypti (1)

c.

Nyamuk Culex (0)

4.

Menurut anda bagaimana gejala penyakit malaria?

a.

Demam panas, mengigigil (0)

b.

Demam panas, mengigigil, berkeringat dan disertai sakit kepala, mual

dan muntah (2)

c.

Demam panas, terdapat bintik-bintik merah di kulit (1)

5.

Dimana nyamuk malaria bersarang?

a.

Air mengalir seperti sungai (0)

b.

Air yang tergenang dan memiliki dasar tanah seperti rawa-rawa dan

kolam ikan (2)

c.

Air yang terdapat di dalam wadah seperti tong air, tempayan, bak

mandi yang terbuat dari semen dan kaleng bekas (1)

6.

Menurut anda siapa saja yang dapat terkena penyakit malaria?

a.

Semua golongan umur (2)

b.

Hanya terjadi pada orang yang bekerja di tengah hutan (0)

c.

Dapat terjadi pada bayi dan ibu hamil (1)

7.

Dimanakah nyamuk malaria suka hinggap?

a.

Di bak mandi (0)

(3)

b.

Menutup tempayan dan mengubur barang-barang bekas (0)

c.

Memasang kawat kasa pada ventilasi rumah, menggunakan kelambu

pada saat tidur di malam hari, menggunakan obat nyamuk bakar atau

semprot, apabila keluar pada malam hari selalu menggunakan obat

nyamuk oles dan pakaian tertutup serta menghindari keluar pada

malam hari (2)

9.

Menurut anda, kapan nyamuk malaria menggigit manusia?

a.

Senja hingga malam hari (2)

b.

Pagi hari dan sore hari (0)

c.

Ketika tidur di malam hari (1)

10.

Menurut anda, jenis ikan apa saja yang memakan jentik nyamuk penyebab

malaria?

a.

Kepala timah, nila, gabus, mujair (2)

b.

Nila dan gabus (1)

c.

Tidak tahu (0)

C.

SIKAP

No Pernyataan

SS

S

TS

STS

1

Penyakit malaria adalah salah satu penyakit

yang harus diberantas dan diwaspadai oleh

masyarakat

(4)

(3)

(2)

(1)

2

Saya akan melakukan pencegahan

penularan penyakit malaria dengan

menjaga kebersihan rumah dan lingkungan

sekitarnya.

(4)

(3)

(2)

(1)

3

Saya akan mengikuti penyuluhan dari petugas

kesehatan tentang penyakit malaria,

selanjutnya saya akan melaksanakan tindakan

pencegahan

malaria.

(4)

4

Saya lebih menyukai pencegahan terhadap

gigitan nyamuk penyebab malaria daripada

mengobati setelah sakit

(4)

(3)

(2)

(1)

5

Saya akan menggunakan kelambu ketika

tidur di malam hari untuk mencegah

penyakit malaria

(4)

(3)

(2)

(1)

6

Saya akan melakukan pencegahan penyakit

malaria jika di lingkungan tempat tinggal

sudah ada penderita malaria

(1)

(2)

(3)

(4)

7

Jika saya merasakan gejala penyakit

malaria maka saya akan membiarkan saja.

(1)

(2)

(3)

(4)

8

Saya akan membiarkan genangan air yang

berada di sekitar rumah

(1)

(2)

(3)

(4)

9

Saya hanya perlu membersihkan dan

menjaga lingkungan rumah saya agar

terhindar dari penyakit malaria

(4)

(3)

(2)

(1)

10 Saya tidak memasang kawat kasa pada

ventilasi karena tidak ada hubungannya

dengan penyakit malaria

(1)

(2)

(3)

(4)

11 Saya akan keluar pada malam hari dengan

menggunakan pakaian tertutup dan panjang

untuk mencegaha penyakit malaria

(4)

(3)

(2)

(1)

12 Saya akan mengajak tetangga untuk

sama-sama menjaga dan membersihkan

lingkungan rumah masing-masing agar

terhindar dari penyakit malaria.

(4)

(3)

(2)

(1)

D.

TINDAKAN

No

Pernyataan

Ya

Tidak

1

Apakah anda menggunakan kawat kasa pada ventilasi

rumah?

(1)

(0)

2

Apakah anda menggunakan kelambu pada saat tidur

malam hari?

(1)

(0)

3

Apakah anda menggunakan obat anti nyamuk pada

saat tidur malam hari?

(1)

(0)

4

Apakah anda menggunakan baju lengan panjang ketika

keluar rumah pada malam hari?

(1)

(0)

5

Apakah anda menggunakan obat nyamuk oles pada

saat keluar malam hari?

(5)

sekitar?

8

Apakah anda menghadiri kegiatan penyuluhan yang

dilakukan oleh petugas kesehatan yang diadakan di

lingkungan rumah anda?

(1)

(0)

9

Apakah anda membiarkan apabila terdapat tempat

yang dapat menimbulkan genangan air?

(0)

(1)

10

Apakah anda mengikuti kegiatan royong yang

dilakukan di lingkungan anda?

(1)

(0)

11

Apakah anda pernah membersihkan semak-semak /

kandang ternak di sekitar lingkungan rumah anda?

(6)

Lampiran Observasi

Lembar Observasi

PENGARUH FAKTOR LINGKUNGAN DAN PERILAKU TERHADAP

KEJADIAN MALARIA DI KECAMATAN SIABU

KABUPATEN MANDAILING NATAL

TAHUN 2015

No. Rumah

:

Desa

:

Tanggal Observasi

:

E.

IDENTITAS RESPONDEN

a.

Nama

:

b.

Umur

:

c.

Jenis Kelamin : 1. Laki-laki 2. Wanita

d.

Pekerjaan

: 1. Petani

2. Nelayan

3. Pedagang

4. Pegawai Swasta

5. PNS/TNI/POLRI

F.

FAKTOR LINGKUNGAN

1.

Lingkungan luar rumah

Ada

Tidak ada

a.

Genangan air

b.

Parit atau selokan

c.

Rawa-rawa

Ada

Tidak ada

(7)

mm

(8)

Lampiran Output

Crosstabs

GA * Kasus

Crosstab

21 9 30

70,0% 30,0% 100,0%

10 22 32

31,3% 68,8% 100,0%

31 31 62

50,0% 50,0% 100,0%

Count Tidak Ada

Ada GA

Total

Kontrol Kasus

Kasus

Total

Chi-Square Tests

9,300b 1 ,002 ,005 ,002

7,815 1 ,005

9,549 1 ,002 ,005 ,002

,005 ,002

9,150c 1 ,002 ,005 ,002 ,002

62 Pearson Chi-Square

Continuity Correctiona

Likelihood Ratio Fis her's Exact Test Linear-by-Linear As sociation N of Valid Cases

Value df

As ymp. Sig. (2-sided)

Exact Sig. (2-sided)

Exact Sig. (1-sided)

Point Probability

Computed only for a 2x2 table a.

0 cells (,0%) have expected count les s than 5. The minimum expected count is 15,00. b.

(9)

5,133 1,742 15,131

2,240 1,273 3,940

,436 ,241 ,791

62 Odds Ratio for GA

(Tidak Ada / Ada) For cohort Kasus = Kontrol For cohort Kasus = Kasus

N of Valid Cases

Value Lower Upper

Parit * Kasus

Crosstab

17 10 27

63,0% 37,0% 100,0%

14 21 35

40,0% 60,0% 100,0%

31 31 62

50,0% 50,0% 100,0%

Count % within Parit Count % within Parit Count % within Parit Tidak Ada

Ada Parit

Total

Kontrol Kasus

Kasus

Total

Chi-Square Tests

3,215b 1 ,073 ,124 ,062

2,362 1 ,124

3,245 1 ,072 ,124 ,062

,124 ,062

3,163c 1 ,075 ,124 ,062 ,042

62 Pearson Chi-Square

Continuity Correctiona

Likelihood Ratio Fis her's Exact Test Linear-by-Linear As sociation N of Valid Cases

Value df

As ymp. Sig. (2-sided)

Exact Sig. (2-sided)

Exact Sig. (1-sided)

Point Probability

Computed only for a 2x2 table a.

0 cells (,0%) have expected count les s than 5. The minimum expected count is 13,50. b.

(10)

Risk Estimate

2,550 ,907 7,165

1,574 ,956 2,591

,617 ,352 1,082

62 Odds Ratio for Parit

(Tidak Ada / Ada) For cohort Kasus = Kontrol

For cohort Kasus = Kasus

N of Valid Cases

Value Lower Upper

95% Confidence Interval

Sawah * Kasus

Crosstab

21 12 33

63,6% 36,4% 100,0%

10 19 29

34,5% 65,5% 100,0%

31 31 62

50,0% 50,0% 100,0%

Count

% within Sawah Count

% within Sawah Count

% within Sawah Tidak Ada

Ada Sawah

Total

Kontrol Kasus

Kasus

Total

Chi-Square Tests

5,248b 1 ,022 ,041 ,020

4,146 1 ,042

5,326 1 ,021 ,041 ,020

,041 ,020

5,163c 1 ,023 ,041 ,020 ,015

62 Pearson Chi-Square

Continuity Correctiona

Likelihood Ratio Fis her's Exact Test Linear-by-Linear As sociation N of Valid Cases

Value df

As ymp. Sig. (2-sided)

Exact Sig. (2-sided)

Exact Sig. (1-sided)

Point Probability

Computed only for a 2x2 table a.

0 cells (,0%) have expected count les s than 5. The minimum expected count is 14,50. b.

(11)

3,325 1,171 9,442

1,845 1,050 3,244

,555 ,329 ,936

62 Odds Ratio for Sawah

(Tidak Ada / Ada) For cohort Kasus = Kontrol

For cohort Kasus = Kasus

N of Valid Cases

Value Lower Upper

Semak * Kasus

Crosstab

20 15 35

57,1% 42,9% 100,0%

11 16 27

40,7% 59,3% 100,0%

31 31 62

50,0% 50,0% 100,0%

Count

% within Semak Count

% within Semak Count

% within Semak Tidak Ada

Ada Semak

Total

Kontrol Kasus

Kasus

Total

Chi-Square Tests

1,640b 1 ,200 ,306 ,153

1,050 1 ,306

1,648 1 ,199 ,306 ,153

,306 ,153

1,614c 1 ,204 ,306 ,153 ,091

62 Pearson Chi-Square

Continuity Correctiona

Likelihood Ratio Fis her's Exact Test Linear-by-Linear As sociation N of Valid Cases

Value df

As ymp. Sig. (2-sided)

Exact Sig. (2-sided)

Exact Sig. (1-sided)

Point Probability

Computed only for a 2x2 table a.

0 cells (,0%) have expected count les s than 5. The minimum expected count is 13,50. b.

(12)

Risk Estimate

1,939 ,700 5,371

1,403 ,819 2,402

,723 ,441 1,185

62 Odds Ratio for Semak

(Tidak Ada / Ada) For cohort Kasus = Kontrol

For cohort Kasus = Kasus

N of Valid Cases

Value Lower Upper

95% Confidence Interval

Ternak * Kasus

Crosstab

17 14 31

54,8% 45,2% 100,0%

14 17 31

45,2% 54,8% 100,0%

31 31 62

50,0% 50,0% 100,0%

Count

% within Ternak Count

% within Ternak Count

% within Ternak Tidak Ada

Ada Ternak

Total

Kontrol Kasus

Kasus

Total

Chi-Square Tests

,581b 1 ,446 ,612 ,306

,258 1 ,611

,582 1 ,446 ,612 ,306

,612 ,306

,571c 1 ,450 ,612 ,306 ,151

62 Pearson Chi-Square

Continuity Correctiona

Likelihood Ratio Fis her's Exact Test Linear-by-Linear As sociation N of Valid Cases

Value df

As ymp. Sig. (2-sided)

Exact Sig. (2-sided)

Exact Sig. (1-sided)

Point Probability

Computed only for a 2x2 table a.

0 cells (,0%) have expected count les s than 5. The minimum expected count is 15,50. b.

(13)

1,474 ,542 4,010

1,214 ,735 2,007

,824 ,498 1,361

62 Odds Ratio for Ternak

(Tidak Ada / Ada) For cohort Kasus = Kontrol

For cohort Kasus = Kasus

N of Valid Cases

Value Lower Upper

KK * Kasus

Crosstab

24 10 34

70,6% 29,4% 100,0%

7 21 28

25,0% 75,0% 100,0%

31 31 62

50,0% 50,0% 100,0%

Count

Tidak Ada KK

Total

Kontrol Kasus

Kasus

Total

Chi-Square Tests

12,765b 1 ,000 ,001 ,000

11,006 1 ,001

13,265 1 ,000 ,001 ,000

,001 ,000

12,559c 1 ,000 ,001 ,000 ,000

62 Pearson Chi-Square

Continuity Correctiona

Likelihood Ratio Fis her's Exact Test Linear-by-Linear As sociation N of Valid Cases

Value df

As ymp. Sig. (2-sided)

Exact Sig. (2-sided)

Exact Sig. (1-sided)

Point Probability

Computed only for a 2x2 table a.

0 cells (,0%) have expected count les s than 5. The minimum expected count is 14,00. b.

(14)

Risk Estimate

7,200 2,327 22,279

2,824 1,434 5,558

,392 ,223 ,689

62 Odds Ratio for KK

(Ada / Tidak Ada) For cohort Kasus = Kontrol For cohort Kasus = Kasus

N of Valid Cases

Value Lower Upper

95% Confidence Interval

KD * Kasus

Crosstab

21 24 45

46,7% 53,3% 100,0%

10 7 17

58,8% 41,2% 100,0%

31 31 62

50,0% 50,0% 100,0%

Count Memenuhi Syarat

Tidak Memenuhi syarat KD

Total

Kontrol Kasus

Kasus

Total

Chi-Square Tests

,729b 1 ,393 ,570 ,285

,324 1 ,569

,732 1 ,392 ,570 ,285

,570 ,285

,718c 1 ,397 ,570 ,285 ,158

62 Pearson Chi-Square

Continuity Correctiona

Likelihood Ratio Fis her's Exact Test Linear-by-Linear As sociation N of Valid Cases

Value df

As ymp. Sig. (2-sided)

Exact Sig. (2-sided)

Exact Sig. (1-sided)

Point Probability

Computed only for a 2x2 table a.

0 cells (,0%) have expected count les s than 5. The minimum expected count is 8,50. b.

(15)

,613 ,198 1,895

,793 ,478 1,315

1,295 ,690 2,433

62 Odds Ratio for KD

(Memenuhi Syarat / Tidak Memenuhi syarat) For cohort Kasus = Kontrol

For cohort Kasus = Kasus

N of Valid Cases

Value Lower Upper

LR * Kasus

Crosstab

20 14 34

58,8% 41,2% 100,0%

11 17 28

39,3% 60,7% 100,0%

31 31 62

50,0% 50,0% 100,0%

Count Memenuhi Syarat

Tidak Memenuhi syarat LR

Total

Kontrol Kasus

Kasus

Total

Chi-Square Tests

2,345b 1 ,126 ,202 ,101

1,628 1 ,202

2,360 1 ,124 ,202 ,101

,202 ,101

2,307c 1 ,129 ,202 ,101 ,064

62 Pearson Chi-Square

Continuity Correctiona

Likelihood Ratio Fis her's Exact Test Linear-by-Linear As sociation N of Valid Cases

Value df

As ymp. Sig. (2-sided)

Exact Sig. (2-sided)

Exact Sig. (1-sided)

Point Probability

Computed only for a 2x2 table a.

0 cells (,0%) have expected count les s than 5. The minimum expected count is 14,00. b.

(16)

Risk Estimate

2,208 ,796 6,126

1,497 ,873 2,568

,678 ,411 1,118

62 Odds Ratio for LR

(Memenuhi Syarat / Tidak Memenuhi syarat) For cohort Kasus = Kontrol

For cohort Kasus = Kasus

N of Valid Cases

Value Lower Upper

95% Confidence Interval

Pakaian * Kasus

Crosstab

19 20 39

48,7% 51,3% 100,0%

12 11 23

52,2% 47,8% 100,0%

31 31 62

50,0% 50,0% 100,0%

Count

% within Pakaian Count

% within Pakaian Count

% within Pakaian Tidak Ada

Ada Pakaian

Total

Kontrol Kasus

Kasus

Total

Chi-Square Tests

,069b 1 ,793 1,000 ,500

,000 1 1,000

,069 1 ,793 1,000 ,500

1,000 ,500

,068c 1 ,794 1,000 ,500 ,200

62 Pearson Chi-Square

Continuity Correctiona

Likelihood Ratio Fis her's Exact Test Linear-by-Linear As sociation N of Valid Cases

Value df

As ymp. Sig. (2-sided)

Exact Sig. (2-sided)

Exact Sig. (1-sided)

Point Probability

Computed only for a 2x2 table a.

0 cells (,0%) have expected count les s than 5. The minimum expected count is 11,50. b.

(17)

,871 ,310 2,442

,934 ,563 1,550

1,072 ,634 1,813

62 Odds Ratio for Pakaian

(Tidak Ada / Ada) For cohort Kasus = Kontrol

For cohort Kasus = Kasus

N of Valid Cases

Value Lower Upper

Kat_Pengetahuan * Kasus

Crosstab

7 3 10

70,0% 30,0% 100,0%

24 28 52

46,2% 53,8% 100,0%

31 31 62

50,0% 50,0% 100,0%

Count % within Kat_ Pengetahuan Count % within Kat_ Pengetahuan Count % within Kat_ Pengetahuan Baik

Buruk Kat_Pengetahuan

Total

Kontrol Kasus

Kasus

Total

Chi-Square Tests

1,908b 1 ,167 ,301 ,150

1,073 1 ,300

1,954 1 ,162 ,301 ,150

,301 ,150

1,877c 1 ,171 ,301 ,150 ,110

62 Pearson Chi-Square

Continuity Correctiona

Likelihood Ratio Fis her's Exact Test Linear-by-Linear As sociation N of Valid Cases

Value df

As ymp. Sig. (2-sided)

Exact Sig. (2-sided)

Exact Sig. (1-sided)

Point Probability

Computed only for a 2x2 table a.

0 cells (,0%) have expected count les s than 5. The minimum expected count is 5,00. b.

(18)

Risk Estimate

2,722 ,633 11,701

1,517 ,919 2,503

,557 ,209 1,484

62 Odds Ratio for

Kat_Pengetahuan (Baik / Buruk) For cohort Kasus = Kontrol For cohort Kasus = Kasus

N of Valid Cases

Value Lower Upper

95% Confidence Interval

Kat_Sikap * Kasus

Crosstab

24 16 40

60,0% 40,0% 100,0%

7 15 22

31,8% 68,2% 100,0%

31 31 62

50,0% 50,0% 100,0%

Count

% within Kat_Sikap Count

% within Kat_Sikap Count

% within Kat_Sikap Baik

Buruk Kat_

Sikap

Total

Kontrol Kasus

Kasus

Total

Chi-Square Tests

4,509b 1 ,034 ,062 ,031

3,452 1 ,063

4,588 1 ,032 ,062 ,031

,062 ,031

4,436c 1 ,035 ,062 ,031 ,023

62 Pearson Chi-Square

Continuity Correctiona

Likelihood Ratio Fis her's Exact Test Linear-by-Linear As sociation N of Valid Cases

Value df

As ymp. Sig. (2-sided)

Exact Sig. (2-sided)

Exact Sig. (1-sided)

Point Probability

Computed only for a 2x2 table a.

0 cells (,0%) have expected count les s than 5. The minimum expected count is 11,00. b.

(19)

3,214 1,072 9,634

1,886 ,973 3,656

,587 ,365 ,943

62 Odds Ratio for Kat_

Sikap (Baik / Buruk) For cohort Kasus = Kontrol

For cohort Kasus = Kasus

N of Valid Cases

Value Lower Upper

Kat_Tindakan * Kasus

Crosstab

8 7 15

53,3% 46,7% 100,0%

23 24 47

48,9% 51,1% 100,0%

31 31 62

50,0% 50,0% 100,0%

Count

% within Kat_Tindakan Count

% within Kat_Tindakan Count

% within Kat_Tindakan Baik

Buruk Kat_Tindakan

Total

Kontrol Kasus

Kasus

Total

Chi-Square Tests

,088b 1 ,767 1,000 ,500

,000 1 1,000

,088 1 ,767 1,000 ,500

1,000 ,500

,087c 1 ,769 1,000 ,500 ,223

62 Pearson Chi-Square

Continuity Correctiona

Likelihood Ratio Fis her's Exact Test Linear-by-Linear As sociation N of Valid Cases

Value df

As ymp. Sig. (2-sided)

Exact Sig. (2-sided)

Exact Sig. (1-sided)

Point Probability

Computed only for a 2x2 table a.

0 cells (,0%) have expected count les s than 5. The minimum expected count is 7,50. b.

(20)

Risk Estimate

1,193 ,372 3,821

1,090 ,625 1,901

,914 ,497 1,680

62 Odds Ratio for Kat_

Tindakan (Baik / Buruk) For cohort Kasus = Kontrol

For cohort Kasus = Kasus

N of Valid Cases

Value Lower Upper

95% Confidence Interval

LOGISTIC REGRESSION VARIABLES Kasus

/METHOD = ENTER GA Parit Sawah KK LR Kat_Pengetahuan Kat_Sikap

/PRINT = CI(95)

/CRITERIA = PIN(.05) POUT(.10) ITERATE(20) CUT(.5) .

Logistic Regression

Case Processing Summary

62 100,0

0 ,0

62 100,0

0 ,0

62 100,0

Unweighted Casesa

Included in Analysis Mis sing Cases Total

Selected Cases

Unselected Cas es Total

N Percent

If weight is in effect, s ee class ification table for the total number of cases.

a.

De pendent V aria ble Encodi ng

0 1 Original Value

Kontrol Kasus

(21)

0 31 ,0

Overall Percentage Step 0

Kontrol Kasus

Kasus Percentage

Correct Predicted

Constant is included in the model. a.

The cut value is ,500 b.

Va riables in the Equa tion

,000 ,254 ,000 1 1,000 1,000

Constant St ep 0

B S. E. W ald df Sig. Ex p(B )

Variables not in the Equation

9,300 1 ,002

3,215 1 ,073

5,248 1 ,022

12,765 1 ,000

2,345 1 ,126

1,908 1 ,167

4,509 1 ,034

24,954 7 ,001

GA

Overall Statistics Step

0

Score df Sig.

Block 1: Method = Enter

Omnibus Tests of Model Coefficients

30,849 7 ,000

30,849 7 ,000

30,849 7 ,000

Step Block Model Step 1

(22)

Model Summary

55,101a ,392 ,523

Step 1

-2 Log likelihood

Cox & Snell R Square

Nagelkerke R Square

Es timation terminated at iteration number 5 because parameter estimates changed by les s than ,001. a.

Classification Tablea

25 6 80,6

Overall Percentage Step 1

Kontrol Kasus

Kasus Percentage

Correct Predicted

The cut value is ,500 a.

Va riables in the Equa tion

1,357 ,744 3,328 1 ,068 3,884 ,904 16,683 ,526 ,880 ,358 1 ,550 1,693 ,302 9,499 ,995 ,942 1,115 1 ,291 2,705 ,427 17,147 2,407 ,766 9,864 1 ,002 11,095 2,471 49,813 ,836 ,718 1,354 1 ,245 2,307 ,564 9,426 ,984 ,893 1,215 1 ,270 2,676 ,465 15,396 1,290 ,758 2,896 1 ,089 3,631 ,822 16,038 -4,059 1,255 10,454 1 ,001 ,017

GA 95,0% C.I.for EXP(B)

Variable(s) entered on step 1: GA, Parit, Sawah, KK, LR, Kat_Pengetahuan, Kat_Sik ap. a.

LOGISTIC REGRESSION VARIABLES Kasus

/METHOD = ENTER GA Sawah KK LR Kat_Pengetahuan Kat_Sikap

/PRINT = CI(95)

/CRITERIA = PIN(.05) POUT(.10) ITERATE(20) CUT(.5) .

(23)

0 ,0

62 100,0

0 ,0

62 100,0

Mis sing Cases Total

Unselected Cas es Total

If weight is in effect, s ee class ification table for the total number of cases.

a.

De pendent V aria ble Encodi ng

0 1 Original Value

Kontrol Kasus

Int ernal Value

Block 0: Beginning Block

Classification Tablea,b

0 31 ,0

0 31 100,0

50,0 Observed

Kontrol Kasus Kasus

Overall Percentage Step 0

Kontrol Kasus

Kasus Percentage

Correct Predicted

Constant is included in the model. a.

The cut value is ,500 b.

Va riables in the Equa tion

,000 ,254 ,000 1 1,000 1,000

Constant St ep 0

(24)

Variables not in the Equation

9,300 1 ,002

5,248 1 ,022

12,765 1 ,000

2,345 1 ,126

1,908 1 ,167

4,509 1 ,034

24,877 6 ,000

GA

Overall Statistics Step

0

Score df Sig.

Block 1: Method = Enter

Omnibus Tests of Model Coefficients

30,493 6 ,000

30,493 6 ,000

30,493 6 ,000

Step Block Model Step 1

Chi-square df Sig.

Model Summary

55,457a ,388 ,518

Step 1

-2 Log likelihood

Cox & Snell R Square

Nagelkerke R Square

Es timation terminated at iteration number 5 because parameter estimates changed by les s than ,001. a.

Classification Tablea

25 6 80,6

Overall Percentage Step 1

Kontrol Kasus

Kasus Percentage

Correct Predicted

The cut value is ,500 a.

(25)

1,309 ,808 2,622 1 ,105 3,702 ,759 18,055 2,382 ,761 9,807 1 ,002 10,823 2,438 48,053 ,729 ,686 1,128 1 ,288 2,073 ,540 7,954 ,938 ,897 1,093 1 ,296 2,555 ,440 14,824 1,283 ,747 2,949 1 ,086 3,608 ,834 15,603 -3,799 1,137 11,160 1 ,001 ,022

Sawah KK LR

Kat_Pengetahuan Kat_Sikap Constant 1a

Variable(s) entered on step 1: GA, Sawah, KK, LR, Kat_Pengetahuan, Kat_Sikap. a.

LOGISTIC REGRESSION VARIABLES Kasus

/METHOD = ENTER GA Sawah KK LR Kat_Sikap

/PRINT = CI(95)

/CRITERIA = PIN(.05) POUT(.10) ITERATE(20) CUT(.5) .

Logistic Regression

Case Processing Summary

62 100,0

0 ,0

62 100,0

0 ,0

62 100,0

Unweighted Casesa

Included in Analysis Mis sing Cases Total

Selected Cases

Unselected Cas es Total

N Percent

If weight is in effect, s ee class ification table for the total number of cases.

a.

De pendent V aria ble Encodi ng

0 1 Original Value

Kontrol Kasus

(26)

Block 0: Beginning Block

Classification Tablea,b

0 31 ,0

Overall Percentage Step 0

Kontrol Kasus

Kasus Percentage

Correct Predicted

Constant is included in the model. a.

The cut value is ,500 b.

Va riables in the Equa tion

,000 ,254 ,000 1 1,000 1,000

Constant St ep 0

B S. E. W ald df Sig. Ex p(B )

Va riables not in the Equa tion

9,300 1 ,002

5,248 1 ,022

12,765 1 ,000

2,345 1 ,126

4,509 1 ,034

23,859 5 ,000

GA Sawah KK LR Kat_S ikap Variables

Overall Statistics St ep

0

Sc ore df Sig.

Block 1: Method = Enter

Omnibus Tests of Model Coefficients

29,340 5 ,000

29,340 5 ,000

29,340 5 ,000

Step Block Model Step 1

(27)

56,610 ,377 ,503 1

Es timation terminated at iteration number 5 because parameter estimates changed by les s than ,001. a.

Classification Tablea

27 4 87,1

7 24 77,4

82,3 Observed

Kontrol Kasus Kasus

Overall Percentage Step 1

Kontrol Kasus

Kasus Percentage

Correct Predicted

The cut value is ,500 a.

Variables in the Equation

1,356 ,732 3,431 1 ,064 3,880 ,924 16,292

1,442 ,801 3,245 1 ,072 4,231 ,881 20,320

2,337 ,752 9,665 1 ,002 10,347 2,372 45,147

,757 ,677 1,250 1 ,264 2,132 ,566 8,037

1,311 ,736 3,172 1 ,075 3,711 ,877 15,708

-3,111 ,884 12,390 1 ,000 ,045

GA Sawah KK LR Kat_Sikap Constant Step

1a

B S.E. Wald df Sig. Exp(B) Lower Upper

95,0% C.I.for EXP(B)

Variable(s) entered on step 1: GA, Sawah, KK, LR, Kat_Sikap. a.

LOGISTIC REGRESSION VARIABLES Kasus

/METHOD = ENTER GA Sawah KK Kat_Sikap

/PRINT = CI(95)

(28)

Logistic Regression

Case Processing Summary

62 100,0

0 ,0

62 100,0

0 ,0

62 100,0

Unweighted Casesa

Included in Analysis Mis sing Cases Total

Selected Cases

Unselected Cas es Total

N Percent

If weight is in effect, s ee class ification table for the total number of cases.

a.

De pendent V aria ble Encodi ng

0 1 Original Value

Kontrol Kasus

Int ernal Value

Block 0: Beginning Block

Classification Tablea,b

0 31 ,0

Overall Percentage Step 0

Kontrol Kasus

Kasus Percentage

Correct Predicted

Constant is included in the model. a.

The cut value is ,500 b.

Va riables in the Equa tion

,000 ,254 ,000 1 1,000 1,000

Constant St ep 0

(29)

5,248 1 ,022

12,765 1 ,000

4,509 1 ,034

23,390 4 ,000

Sawah KK Kat_S ikap Overall Statistics

0

Block 1: Method = Enter

Omnibus Tests of Model Coefficients

28,060 4 ,000

28,060 4 ,000

28,060 4 ,000

Step Block Model Step 1

Chi-square df Sig.

Model Summary

57,891a ,364 ,485

Step 1

-2 Log likelihood

Cox & Snell R Square

Nagelkerke R Square

Es timation terminated at iteration number 5 because parameter estimates changed by les s than ,001. a.

Classification Tablea

28 3 90,3

Overall Percentage Step 1

Kontrol Kasus

Kasus Percentage

Correct Predicted

(30)

Variables in the Equation

1,369 ,722 3,594 1 ,058 3,930 ,955 16,176

1,340 ,768 3,046 1 ,081 3,819 ,848 17,197

2,309 ,731 9,982 1 ,002 10,069 2,403 42,188

1,233 ,727 2,875 1 ,090 3,430 ,825 14,260

-2,717 ,755 12,965 1 ,000 ,066

GA

B S.E. Wald df Sig. Exp(B) Lower Upper

95,0% C.I.for EXP(B)

Variable(s) entered on step 1: GA, Sawah, KK, Kat_Sikap. a.

LOGISTIC REGRESSION VARIABLES Kasus

/METHOD = ENTER GA Sawah KK

/PRINT = CI(95)

/CRITERIA = PIN(.05) POUT(.10) ITERATE(20) CUT(.5) .

Logistic Regression

Case Processing Summary

62 100,0

0 ,0

62 100,0

0 ,0

62 100,0

Unweighted Casesa

Included in Analysis Mis sing Cases Total

Selected Cases

Unselected Cas es Total

N Percent

If weight is in effect, s ee class ification table for the total number of cases.

a.

De pendent V aria ble Encodi ng

0 1 Original Value

Kontrol Kasus

(31)

0 31 ,0

0 31 100,0

50,0 Observed

Kontrol Kasus Kasus

Overall Percentage Step 0

Kontrol Kasus

Kasus Percentage

Correct Predicted

Constant is included in the model. a.

The cut value is ,500 b.

Va riables in the Equa tion

,000 ,254 ,000 1 1,000 1,000

Constant St ep 0

B S. E. W ald df Sig. Ex p(B )

Variables not in the Equation

9,300 1 ,002

5,248 1 ,022

12,765 1 ,000

21,541 3 ,000

GA Sawah KK Variables

Overall Statistics Step

0

Score df Sig.

Block 1: Method = Enter

Omnibus Tests of Model Coefficients

25,031 3 ,000

25,031 3 ,000

25,031 3 ,000

Step Block Model Step 1

(32)

Model Summary

60,920a ,332 ,443

Step 1

-2 Log likelihood

Cox & Snell R Square

Nagelkerke R Square

Es timation terminated at iteration number 5 because parameter estimates changed by les s than ,001. a.

Classification Tablea

21 10 67,7

Overall Percentage Step 1

Kontrol Kasus

Kasus Percentage

Correct Predicted

The cut value is ,500 a.

Va riables in the Equa tion

1,468 ,699 4,408 1 ,036 4,341 1,103 17,095

1,077 ,721 2,233 1 ,135 2,936 ,715 12,058

2,368 ,707 11,214 1 ,001 10,675 2,670 42,683

-2,281 ,669 11,623 1 ,001 ,102

GA

95,0% C.I.for EXP(B)

Variable(s) entered on step 1: GA, Sawah, KK. a.

LOGISTIC REGRESSION VARIABLES Kasus

/METHOD = ENTER GA KK

/PRINT = CI(95)

(33)

62 100,0

0 ,0

62 100,0

0 ,0

62 100,0

Unweighted Cases

Included in Analysis Mis sing Cases Total

Selected Cases

Unselected Cas es Total

N Percent

If weight is in effect, s ee class ification table for the total number of cases.

a.

De pendent V aria ble Encodi ng

0 1 Original Value

Kontrol Kasus

Int ernal Value

Block 0: Beginning Block

Classification Tablea,b

0 31 ,0

Overall Percentage Step 0

Kontrol Kasus

Kasus Percentage

Correct Predicted

Constant is included in the model. a.

The cut value is ,500 b.

Va riables in the Equa tion

,000 ,254 ,000 1 1,000 1,000

Constant St ep 0

(34)

Variables not in the Equation

9,300 1 ,002

12,765 1 ,000

20,079 2 ,000

GA KK Variables

Overall Statistics Step

0

Score df Sig.

Block 1: Method = Enter

Omnibus Tests of Model Coefficients

22,726 2 ,000

22,726 2 ,000

22,726 2 ,000

Step Block Model Step 1

Chi-square df Sig.

Model Summary

63,224a ,307 ,409

Step 1

-2 Log likelihood

Cox & Snell R Square

Nagelkerke R Square

Es timation terminated at iteration number 5 because parameter estimates changed by les s than ,001. a.

Classification Tablea

24 7 77,4

Overall Percentage Step 1

Kontrol Kasus

Kasus Percentage

Correct Predicted

The cut value is ,500 a.

Variables in the Equation

1,867 ,654 8,155 1 ,004 6,469 1,796 23,302 2,179 ,659 10,920 1 ,001 8,837 2,427 32,181 -1,935 ,598 10,458 1 ,001 ,144

GA KK Constant Step

1a

B S.E. Wald df Sig. Exp(B) Lower Upper

95,0% C.I.for EXP(B)

Figur

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Referensi

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