Lampiran 1 LEMBAR OBSERVASI PENGUMPULAN DATA PENGARUH FAKTOR RISIKO TERHADAP KEBERADAAN VEKTOR PENYAKIT DI KAPAL PADA PELABUHAN TEMBILAHAN Nama Kapal
:
Besar Kapal
:
Bendera
:
Tanggal SSCEC
:
Jenis Kapal
:
A. DECK Penilaian No
Komponen yang dinilai
1
Kebersihan (Tidak ada sampah, oli )
2
Lantai kedap air, tidak ada genangan air
3
Lantai tidak berkarat
4
Lantai rata, sambungan tidak menonjol
5
Barang-barang APD, tali tersusun rapi
Keberadaan Vektor
Tdk baik
Baik
.Ada
T.Ada
(0)
(1)
(1)
(2)
Total Nilai
B. KAMAR AWAK KAPAL Penilaian No
1
Komponen yang dinilai
Keberadaan Vektor
Tdk baik
Baik
.Ada
T.Ada
(0)
(1)
(1)
(2)
Kebersihan (tidak ada sampah, barangbarang tersusun rapi)
2
Ventilasi cukup (sirkulasi udara lancar, mempunyai lubang bukaan 1,25 cm)
3
Penerangan >5-10 fc
4
Hunian kamar <4 orang/kamar Total Nilai
Universitas Sumatera Utara
C. KAMAR MANDI/TOILET Penilaian No
1
Komponen yang dinilai
Keberadaan Vektor
Tdk baik
Baik
.Ada
T.Ada
(0)
(1)
(1)
(2)
Kebersihan (Lantai tidak licin, dinding tidak kotor)
2
Tidak berbau
3
Bukan tempat penyimpanan barang
4
Kran berfungsi baik
5
Tersedia wastafel
6
Tersedia air panas
7
Tersedia tissue, sabun Total Nilai
D. DAPUR Penilaian No
1
Keberadaan
Komponen yang dinilai
Vektor Tdk baik
Baik
.Ada
T.Ada
(0)
(1)
(1)
(2)
Kebersihan (Tidak ada sampah berserakan, permukaan dinding lembut dan terang)
2
Ada tempat sampah yg memenuhi syarat kes
3
Ada pemisahan sampah organik dan an organik
4
Alat-alat bersih
5
Makanan masak tertutup
6
Ventilasi cukup
7
Pencahayaan 20 fc
8
Mencuci dengan air panas 77 derajat Celcius Total Nilai
Universitas Sumatera Utara
E. GUDANG PERSEDIAAN MAKANAN Penilaian No
1
Komponen yang dinilai
Kebersihan
(Tidak
ada
Keberadaan Vektor
Tdk baik
Baik
.Ada
T.Ada
(0)
(1)
(1)
(2)
sampah
berserakan, barang-barang tersusun rapi) 2
Menyimpan pada rak 15 cm dari deck
3
Tidak berbau
4
Pencahayaan 20 fc
5
Thermometer berfungsi dengan baik
6
Temperatur
bahan
makanan
mudah
membusuk disimpan 0-7 derajat celcius 7
Bahan membusuk
makanan
tidak
mudah
disimpan 10-15 derajat
Celcius Total Nilai
Universitas Sumatera Utara
Lampiran 2 Dokumentasi Hasil Penelitian
Gambar 1: Dapur Kapal
Gambar 2: Dapur kapal
Universitas Sumatera Utara
Gambar 3: Deck Kapal
Gambar 4: Gudang Persediaan Makanan di Kapal
Universitas Sumatera Utara
Gambar 5: Gudang Persediaan Makanan di Kapal
Gambar 6: Toilet di Kapal
Universitas Sumatera Utara
Gambar 7: Toilet di Kapal
Gambar 8: Kapal Kargo Motor Venture
Universitas Sumatera Utara
Gambar 9: Dapur di Kapal
Gambar 10: Toilet di Kapal
Universitas Sumatera Utara
Gambar 11: Toilet di Kapal
Gambar 12: Gudang Persediaan Makanan
Universitas Sumatera Utara
Gambar 13: Kamar Awak kapal
Gambar 14: Deck Kapal
Universitas Sumatera Utara
Gambar 15: Kapal Tug Boat
Universitas Sumatera Utara
Lampiran 3
Daftar kedatangan kapal yang diobservasi pada Kantor Kesehatan Pelabuhan Kelas III Tembilahan Bulan September dan Oktober Tahun 2011 No
Tanggal
Nama kapal
Isi kotor
Bendera
Datang dari
(M3) 1
01 Sept
Tb.Sri jaya Utama
203,76
Indonesia
Singapore
2
05 Sept
Tb.Surya Wira
646,07
Indonesia
Vietnam
3
05 Sept
Klm.Rajawali Sakti
280,17
Indonesia
Slt.Panjang
4
06 Sept
Mv.Didne
115.073,46
Malaysia
Malaysia
5
07 Sept
Tb.Terus Daya
732,97
Indonesia
Malaysia
6
08 Sept
Tb.Marcopolo 107
464,12
Indonesia
Jambi
7
08 Sept
Tb.Marcopolo 29
339,20
Indonesia
K.Tungkal
8
08 Sept
Mt.Pelumin Satu
4.004,45
Indonesia
Tj.buton
9
09 sept
Tb.Armada Asia
291,49
Indonesia
Tj.Balai
10
10 Sept
Tb.TS 293
648.07
Indonesia
Tj.Buton
11
10 Sept
Tb.Maju Daya 21
523,55
Indonesia
Palembang
12
11 Sept
Tb.Tri Daya Aruna
263,19
Indonesia
Tj.Balai K
13
12 Sept
Tb.TS 24.5.1
447,14
Indonesia
Tj.Buton
14
12 Sept
Tb.Asento 296
616,94
Indonesia
Tj.Buton
15
13 Sept
Tb.Surya Cakra 6
721,65
Indonesia
Malaysia
16
13 Sept
Tb.Marcopolo 99
356,58
Indonesia
Batam
17
14 Sept
Tb.Citra Karya
169,80
Indonesia
Tj.Buton
18
15 Sept
Klm.Johnson
251,87
Indonesia
Sumsang
19
15 Sept
Tb.Garuda III
481,10
Indonesia
Tj.Buton
20
16 Sept
Tb.Marcopolo 57
435,83
Indonesia
Jambi
21
17 Sept
Tb.Ocean Arindo
314,13
Indonesia
Tj.Buton
Universitas Sumatera Utara
22
17 Sept
MV.Power Stell
110.033,23
Malaysia
Malaysia
23
18 Sept
Tb.Citra Sanjaya
206,59
Indonesia
Tj.Buton
24
19 Sept
Tb.BPW 3
283,00
Indonesia
Tj.Buton
25
20 Sept
Tb.BPW 5
305,84
Indonesia
Tj.Buton
26
21 Sept
Tb.Arwana
249,04
Indonesia
Tj.Buton
27
22 Sept
Tb.Mitra Kencana
421,67
Indonesia
Dumai
28
23 Sept
Tb.Venus I
229,23
Indonesia
Tj.Buton
29
23 Sept
Tb.Maju Agung
192,44
Indonesia
Tj.Buton
30
24 Sept
Klm.Cahaya Indo
311,30
Indonesia
Sumsang
31
25 Sept
Tb.Jangkat
240,55
Indonesia
Tj.Balai K
32
25 Sept
Tb.Marcopolo 296
3.421,79
Indonesia
Jambi
33
26 Sept
Tb.United I
430,16
Indonesia
Tj.Buton
34
27 Sept
Tb.Amethyss I
247,93
Indonesia
Tj.Buton
35
27 Sept
Tb.Honduras
291,43
Indonesia
Tj.Buton
36
27 Sept
MV.AB Jad
85.049,99
India
India
37
28 Sept
Tb.Marcopolo 107
464,12
Indonesia
K.Tungkal
38
28 Sept
Tb.GMS Fortuna
149,99
Indonesia
Siak
39
29 Sept
Klm.Sinar Maju
367,90
Indonesia
Palembang
40
29 Sept
Klm.Indra Jaya
362,64
Indonesia
Sumsang
41
30 Sept
Klm.Mekar Puspita
1.743,28
Indonesia
Pekanbaru
42
01 Okt
Klm.Victory
223,83
Indonesia
Sumsang
43
03 Okt
Tb.Garnet-I
308,47
Indonesia
Tj.Buton
44
04 Okt
Klm.Fajar
642,41
Indonesia
S.Kelapa
45
05 Okt
Klm.Bina Abadi
837,68
Indonesia
S.Kelapa
46
06 Okt
Tb.Cipta Agung-I
266,02
Indonesia
Kijang
47
07 Okt
Tb.Terus daya-25
732,83
Indonesia
Singapura
48
07 Okt
Tb.Satria Samudra
217,91
Indonesia
Tj.Buton
Universitas Sumatera Utara
49
09 Okt
Km.Duta Samudra
990,5
Indonesia
Slt.Panjang
50
10 Okt
Km.Lucky Star
478,83
Indonesia
Palembang
51
11 Okt
Tb.Hufco Flower
232,72
Indonesia
Tj.Buton
52
13 Okt
Km.Dwi Fortuna
1.013,14
Indonesia
Batam
53
14 Okt
Km.Sejahtera-X
840,15
Indonesia
S.Kelapa
54
15 Okt
Tb.Capricon-18
251,87
Indonesia
Tj.Buton
Universitas Sumatera Utara
Lampiran 4
HASIL OBSERVASI PENGARUH FAKTOR RISIKO TERHADAP KEBERADAAN VEKTOR DI KAPAL
FAKTOR RISIKO DI KAPAL
0
0
0
0
3
Nilai 1
0
1
A
Ad
0
0
1
0
0
0
A
4
5
6
7
1
Nilai 0
1
R 2
2
A
Ad
1
1
1
0
Vektor
0
1
kategori
0
4
Ad
0
1 1 1 0 1 1 5 TR
Ta
2 3 4 5 6 7 8
Penilaian 1
Nilai 0
0
1
4
TR
Ta
0
R
Total nilai
1
3
GUD PERS MAKANAN No Komponen
Vektor
Nilai
2
Penilaian
Kategori
1
No Komponen
Penilaian
Vektor
5
No Komponen
Kategori
4
DAPUR Total nilai
3
KAMAR MANDI/TOILET Vektor
2
Kategori
1
Penilaian
Total nilai
Penilaian
Vektor
No komponen
kategori
pl
Total nilai
DECK
KMR AWAK KAPAL No Komponen
Total nilai
K
2 3 4 5 6 7 Nilai
0 0 1 1 1 0 0 3 A R
Ta
1
1
1
0
3
TR
Ta
1
1
1
0
1
0
0
4
TR
Ta
1
0 0 1 1 1 1 0 5 TR
Ad
0
1 1 1 1 0 0 4 TR
Ad
Ta
1
1
1
0
3
TR
Ta
0
1
1
0
0
0
0
2
A
Ta
0
0 0 1 1 1 0 0 3 A
Ad
0
0 1 0 0 0 0 6 AR
Ad
R 3
0
0
0
1
0
1
A R
4
0
0
0
1
0
1
A
R Ta
1
1
1
1
4
TR
Ta
0
1
1
0
0
0
1
3
R
A
R Ta
1
0 1 1 1 1 1 1 7 TR
Ta
1
0 1 1 1 1 1 6 TR
Ta
R
5
1
1
1
1
0
4
TR
Ta
1
1
1
0
3
TR
Ta
0
1
1
1
0
0
1
4
TR
Ad
1
0 0 1 1 1 0 1 5 TR
Ad
1
0 1 1 0 1 1 5 TR
Ta
6
0
0
0
1
1
2
A
Ta
0
0
1
0
1
A
Ad
0
1
1
0
0
0
0
2
A
Ad
1
0 0 1 1 1 1 0 5 TR
Ad
0
1 0 1 0 0 0 2 Ar
Ad
Ad
0
0 0 1 1 1 1 1 5 TR
Ta
1
1 1 1 0 1 0 5 TR
Ad
Ad
0
0 1 1 1 1 1 0 5 TR
Ta
1
1 1 1 1 1 0 6 TR
Ta
Ad
0
0 0 1 1 1 0 0 3 A
Ad
0
0 0 1 0 0 0 1 AR
Ad
R 7
0
0
0
1
0
1
A
R Ta
0
0
1
0
1
R 8
1
1
0
1
0
3
TR
A
R Ad
0
0
0
0
0
0
1
1
R Ta
0
1
1
1
3
TR
A R
Ad
0
0
0
0
0
0
1
1
A R
9
0
0
0
1
0
1
A R
Ta
0
0
1
0
1
A R
Ad
0
1
1
1
1
0
1
5
TR
R
Universitas Sumatera Utara
10
1
1
1
0
1
4
TR
Ad
1
1
1
0
3
TR
Ta
0
0
1
0
0
0
0
1
A
Ad
1
0 1 1 1 1 1 0 6 TR
Ad
1
1 1 1 1 1 0 6 TR
Ta
Ad
1
0 0 1 1 1 1 1 5 TR
Ad
1
1 1 1 1 0 0 5 TR
Ta
Ta
0
0 0 1 1 0 0 0 2 A
Ad
0
1 0 1 0 0 0 2 AR
Ad
R 11
1
1
1
0
1
4
TR
Ta
0
0
1
0
1
A
Ad
0
0
1
0
0
0
1
2
R 12
1
1
0
1
1
4
TR
Ta
0
0
1
0
1
A
A R
Ad
0
1
1
1
0
0
1
4
TR
R 13
0
1
1
1
1
4
TR
Ad
0
0
1
0
1
A
R Ta
0
0
1
0
0
0
1
2
R 14
0
1
1
1
1
4
TR
Ad
1
1
1
0
3
TR
A
Ad
0
1 0 1 1 1 1 0 5 TR
Ad
1
1 0 1 0 1 1 5 TR
Ad
Ta
0
0 0 1 1 1 0 0 3 A
Ta
0
1 0 0 1 1 1 4 TR
Ad
Ad
1
1 1 1 1 1 0 6 TR
Ta
R Ad
0
0
1
0
0
0
1
2
A R
15
0
1
1
1
1
4
TR
Ta
1
1
1
0
3
TR
Ta
0
0
1
0
0
0
1
2
A
R Ad
0
0 1 1 1 1 1 1 6 TR
R
K pl
Universitas Sumatera Utara
FAKTOR RISIKO DI KAPAL
3
4
5
1
Nilai 16
0
1
1
2
3
4
1
2
3
Nilai 1
1
4
TR
Ta
0
0
1
4
5
6
1
1
1
1
1
5
TR
Ta
0
0
0
Ad
0
0 0 1 1 0 0 1 3
AR
Ad
0 1 1 1 0 0 0 3 AR
Ta
Ad
0
0 0 1 1 0 0 0 2
AR
Ad
0 1 0 0 0 0 0 1 AR
Ad
7
1
Nilai 0
1
A
Ad
0
0
1
0
0
0
A
2 3 4 5 6 7 8
0
0
1
2
A
No Komponen Penilaian
1 2 3 4 5 6 7
Nilai
R 17
Vektor
2
Kategori
1
Penilaian
Vektor
Penilaian
Penilaian
Vektor
Komponen
GUD PERS MAKANAN
Total nilai
No Komponen
Kategori
No Komponen
Kategori
DAPUR Total nilai
KAMAR MANDI/TOILET
Total nilai
Vektor
Vektor
Penilaian
Kategori
Total nilai
No Komponen
Kategori
DECK
Total nilai
KMR AWAK KAPAL No
Nilai
R Ad
0
0
0
0
0
0
1
1
R
A R
18
1
0
1
1
1
4
TR
Ta
0
1
1
1
3
TR
Ad
0
1
1
1
1
0
1
5
TR
Ad
0
0 0 1 0 1 0 1 3
AR
Ad
0 0 1 1 0 0 0 2 AR
Ad
19
1
1
0
1
0
3
TR
Ta
1
1
0
1
3
TR
Ta
0
1
1
1
1
1
1
6
TR
Ta
1
1 0 1 1 1 1 0 6
TR
Ta
0 1 0 1 0 0 0 2 AR
Ad
20
1
0
1
1
1
4
TR
Ad
0
0
1
1
1
A
Ad
0
0
1
0
0
0
1
2
A
Ad
0
0 0 1 0 1 1 0 3
AR
Ad
1 1 1 1 0 1 0 5 TR
Ad
Ta
0
0 0 1 1 1 0 0 3
AR
Ta
1 1 0 0 0 0 0 2 AR
Ad
Ta
1
0 1 1 1 1 1 1 7
TR
Ta
0 0 0 0 0 0 0 0 AR
Ta
R 21
1
1
0
1
1
4
TR
Ta
0
0
1
0
1
A
R Ta
0
0
1
0
0
0
0
1
R 22
0
1
1
1
1
4
TR
Ta
1
1
1
1
4
TR
A R
Ta
0
0
1
0
0
0
1
2
A R
23
0
1
1
1
0
3
TR
Ta
0
0
1
0
1
A
Ta
1
1
1
1
1
0
1
6
TR
Ta
0
0 0 1 1 1 0 0 3
AR
Ta
1 1 0 1 0 0 0 3 AR
Ad
Ta
0
0
1
0
0
0
1
2
A
Ta
0
0 0 1 0 1 1 0 3
AR
Ad
0 0 0 0 1 1 1 3 AR
Ad
Ad
0
0
0
0
0
0
1
1
A
Ad
0
0 0 1 1 0 1 0 3
AR
Ta
0 1 0 0 1 1 0 2 AR
Ad
Ad
0
0
1
0
0
0
1
2
A
Ad
0
0 0 1 1 1 0 0 3
AR
Ad
0 1 0 0 0 1 0 2 AR
Ad
Ad
0
0
1
0
1
0
1
3
Ad
1
0 1 1 1 1 0 1 6
TR
Ta
0 0 0 1 1 0 1 3 AR
Ad
R 24
0
1
1
1
1
4
TR
Ad
1
0
0
0
1
A
25
1
1
0
0
1
3
TR
Ad
0
0
1
0
1
A
26
1
0
1
0
1
3
TR
Ad
0
0
1
0
1
A
27
0
1
1
1
0
3
TR
Ta
0
0
1
0
1
R
R
R
R
R A
R A
Universitas Sumatera Utara
R 28
1
0
1
0
1
3
TR
Ad
0
0
1
0
1
29
1
1
0
1
0
3
TR
Ta
0
1
0
0
1
30
0
1
1
1
0
3
TR
Ad
0
1
1
1
3
A
R Ad
1
1
1
0
1
0
1
5
TR
Ad
0
0 0 1 1 1 0 0 3
AR
Ad
0 1 1 0 0 0 0 2 AR
Ad
Ad
0
0
1
0
0
0
1
2
A
Ad
0
0 0 1 0 0 1 1 3
AR
Ad
0 0 0 1 0 0 0 1 AR
Ad
Ad
0
0
1
0
1
0
1
3
Ad
0
0 0 0 1 1 0 0 2
AR
Ad
1 1 0 0 0 0 0 2 AR
Ad
R A R TR
R A R
Universitas Sumatera Utara
FAKTOR RISIKO DI KAPAL
1
3
TR
32
1
0
1
1
1
4
33
0
1
1
1
0
34
1
1
0
1
35
0
0
1
36
1
1
37
1
38
0
2
3
Ta
1
0
1
1
3
TR
Ad
0
0
1
TR
Ta
1
0
0
0
1
A
Ta
0
0
3
TR
Ta
0
0
1
0
1
Ad
1
0
3
TR
Ta
1
1
1
0
3
TR
Ad
1
1
3
TR
Ta
0
0
1
0
1
A
1
1
0
4
TR
Ad
0
0
0
1
1
0
1
1
1
4
TR
Ta
0
0
1
0
1
1
1
1
1
4
TR
Ad
1
0
0
0
1
1
2 3 4 5 6 7 8
A
Ad
1
0 0 1 1 1 1 0 5
TR
Ad
0
1 0 1 1 1 1 0 5
TR
Ad
1
A
Ad
5
6
7
0
0
0
1
2
1
0
0
0
1
2
A
1
1
1
1
1
1
7
0
0
0
0
0
0
1
6
Ad
0
1
1
0
0
0
1
3
Ta
0
0
1
0
0
0
1
2
Ta
0
0
1
0
0
0
0
1
Ta
0
1
1
0
0
0
0
2
Nilai
4
Vektor
1
1
Kategori
1
Nilai
4
Penilaian
Total nilai
2
Penilaian
GUD PERS MAKANAN No Komponen
Vektor
1
Kategori
0
No Komponen
Penilaian
Total nilai
0
3
No Komponen
Vektor
5
DAPUR Kategori
4
KAMAR MANDI/TOILET Total nilai
31
3
Vektor
2
Penilaian
Kategori
1
KMR AWAK KAPAL No Komponen
Total nilai
Penilaian
Vektor
No Komponen
l
Kategori
Total nilai
DECK Kp
1
2
3 4 5 6 7
Ad
0
0
0 0 1 0 1 2
AR
Ta
TR
Ta
0
0
0 0 0 0 1 6
AR
Ta
1 0 1 1 1 0 0 5
TR
Ta
1
1
0 1 0 0 0 3
AR
Ta
0
0 0 1 1 1 0 0 3
TR
Ad
0
0
0 0 0 0 0 0
AR
Ad
Ad
0
0 1 1 1 1 1 0 5
TR
Ad
0
1
0 1 0 0 0 2
AR
Ad
Ad
1
0 1 1 1 1 1 1 7
TR
Ta
0
0
0 0 0 0 0 0
AR
Ta
Ad
0
0 0 1 1 1 0 0 3
A
Ad
0
1
1 1 0 0 0 3
AR
Ta
Ad
0
0 0 1 1 1 0 0 3
Ad
1
1
0 0 0 0 0 2
AR
Ta
Ad
0
1
0 1 0 0 0 2
AR
Ad
Nilai
Nilai
Nilai
R
R A
R
R
R
R A
R
R A
0
0
1
1
1
3
TR
Ta
0
0
0
1
1
A R
A R
R 39
A R
R A
A
A
R
R Ad
0
0
1
0
0
0
0
1
A R
A R
Ad
0
0 0 1 1 1 0 0 3
A R
Universitas Sumatera Utara
40
1
1
1
1
0
4
TR
Ta
1
0
0
0
1
A
Ad
1
1
1
1
1
1
1
7
TR
Ad
0
0 0 1 1 1 0 0 3
R 41
1
0
1
1
0
3
TR
Ad
1
0
0
0
1
A
0
1
0
1
1
3
TR
Ta
0
1
0
0
1
A
Ta
0
1
1
1
0
0
1
4
1
0
1
1
1
4
TR
Ta
1
0
0
0
1
A
Ad
1
0
1
0
0
0
0
2
TR
Ad
0
0 0 1 1 1 0 0 3
1
1
0
1
0
3
TR
Ta
0
1
0
0
1
A
Ad
0
0
1
0
0
0
0
1
1
0
0
1
1
3
TR
Ta
0
1
0
1
3
TR
1
0 0 0 0 0 2
AR
Ad
A
Ad
1
1
0 0 0 0 0 2
AR
Ad
Ad
0
0 0 1 1 1 0 0 3
A
A
Ad
0
1
1 0 0 0 0 2
AR
Ad
R Ad
1
0 1 1 1 1 1 0 5
TR
Ta
1
0
1 0 0 0 1 3
AR
Ad
Ad
0
0 0 1 0 1 1 0 3
A
Ad
0
1
0 1 0 0 0 2
AR
Ad
Ta
0
1
1 0 0 0 0 2
AR
Ad
R Ad
0
1
1
1
0
0
0
3
R 45
A R
R 44
1
R
R 43
Ad
R
R 42
A
A R
Ta
0
1
1
0
1
1
0
4
TR
R Ad
0
1 1 0 0 0 0 1 3
A R
Universitas Sumatera Utara
FAKTOR RISIKO DI KAPAL
3
1
1
3
TR
Ad
0
0
1
4
5
6
7
1
Nilai 0
1
A
2 3 4 5 6 7 8
Vektor
2
Penilaian
Kategori
0
1
GUD PERS MAKANAN No Komponen
Total nilai
0
4
Vektor
1
3
Nilai
Penilaian
Kategori
46
2
No Komponen
Penilaian
Total nilai
1
No Komponen
Vektor
5
DAPUR Kategori
4
KAMAR MANDI/TOILET Total nilai
3 Nilai
Vektor
2
Penilaian
Kategori
1
KMR AWAK KAPAL No Komponen
Total nilai
Penilaian
Vektor
No Komponen
l
Kategori
Total nilai
DECK Kp
1 2 3 4 5 6 7
Nilai
Nilai
Ta
1
0
0
1
1
1
1
5
TR
Ta
0
1 1 1 0 1 0 1 5
TR
Ad
0 0 0 1 0 0 0 1
AR
Ta
Ta
1
0
0
0
1
1
1
4
TR
Ta
0
1 1 0 0 0 0 1 3
AR
Ta
0 0 0 0 1 0 1 2
AR
Ta
Ad
1
0
0
1
1
1
1
5
TR
Ta
0
0 0 1 1 1 0 0 3
AR
Ad
0 1 1 0 0 0 1 3
AR
Ad
Ad
1
0
0
1
1
1
1
5
TR
Ta
0
0 1 0 0 0 0 1 3
AR
Ta
0 0 0 1 0 0 0 1
AR
Ad
Ta
1
1
1
1
0
0
0
4
TR
Ta
0
0 1 0 0 0 1 1 3
AR
Ta
0 0 0 1 0 0 0 1
AR
Ad
Ta
1
1
1
1
1
1
1
7
TR
Ta
0
0 1 1 1 0 1 1 5
AR
Ad
1 1 0 0 0 0 0 2
AR
Ad
Ta
0
0
1
0
0
0
1
2
A
Ad
1
1 0 1 1 1 1 0 6
TR
Ad
1 1 1 0 0 0 0 3
AR
Ad
R 47
1
0
0
1
1
3
TR
Ta
1
0
0
0
1
A R
48
1
1
1
1
0
4
TR
Ad
0
0
1
0
1
A R
49
1
1
0
1
0
3
TR
Ad
0
0
0
1
1
A R
50
1
1
1
1
0
4
TR
Ad
0
0
1
0
1
A R
51
1
1
1
0
1
4
TR
Ta
0
1
0
0
1
A R
52
1
1
0
1
0
3
TR
Ad
0
1
0
0
1
A R
53
0
0
1
1
1
3
TR
Ta
0
0
1
0
1
A
R Ad
0
1
1
1
1
0
1
5
TR
Ta
0
0 0 1 1 1 0 0 3
AR
Ta
0 1 0 1 0 0 0 2
AR
Ad
Ad
0
1
1
0
0
0
0
2
A
Ad
0
1 1 0 0 0 0 0 2
AR
Ad
0 0 0 1 1 0 1 3
AR
Ad
R 54
1
1
1
1
0
4
TR
Ta
0
0
1
0
1
A R
R
Universitas Sumatera Utara
Ket :- AR (Ada Risiko) - TR (Tidak ada risiko) - Ad (Ada) - Ta (Tidak ada)
Universitas Sumatera Utara
Frequencies deck
Valid
res iko tidak ada resiko Total
Frequency 7 47 54
Percent 13.0 87.0 100.0
Valid Percent 13.0 87.0 100.0
Cumulative Percent 13.0 100.0
vektordeck
Valid
ada tidak ada Total
Frequency 18 36 54
Percent 33.3 66.7 100.0
Valid Percent 33.3 66.7 100.0
Cumul ative Percent 33.3 100.0
kamar awak kapal
Valid
res iko tidak ada resiko Total
Frequency 38 16 54
Percent 70.4 29.6 100.0
Valid Percent 70.4 29.6 100.0
Cumulative Percent 70.4 100.0
vektorkamarawak
Valid
ada tidak ada Total
Frequency 37 17 54
Percent 68.5 31.5 100.0
Valid Percent 68.5 31.5 100.0
Cumul ative Percent 68.5 100.0
toilet
Valid
res iko tidak ada resiko Total
Frequency 35 19 54
Percent 64.8 35.2 100.0
Valid Percent 64.8 35.2 100.0
Cumulative Percent 64.8 100.0
Universitas Sumatera Utara
vektoroilet
Valid
ada tidak ada Total
Frequency 35 19 54
Percent 64.8 35.2 100.0
Valid Percent 64.8 35.2 100.0
Cumul ative Percent 64.8 100.0
dapur
Valid
res iko tidak ada resiko Total
Frequency 32 22 54
Percent 59.3 40.7 100.0
Valid Percent 59.3 40.7 100.0
Cumulative Percent 59.3 100.0
vektordapur
Valid
ada tidak ada Total
Frequency 40 14 54
Percent 74.1 25.9 100.0
Valid Percent 74.1 25.9 100.0
Cumul ative Percent 74.1 100.0
gudang persediaan makanan
Valid
res iko tidak ada resiko Total
Frequency 37 17 54
Percent 68.5 31.5 100.0
Valid Percent 68.5 31.5 100.0
Cumulative Percent 68.5 100.0
vektorgudang
Valid
ada tidak ada Total
Frequency 38 16 54
Percent 70.4 29.6 100.0
Valid Percent 70.4 29.6 100.0
Cumul ative Percent 70.4 100.0
Universitas Sumatera Utara
Crosstabs deck * keberadaan vektor Crosstab
deck
res iko
tidak ada resik o
Total
keberadaan vektor ada tidak ada 6 1 4.8 2.2 85.7% 14.3% 11.1% 1.9% 31 16 32.2 14.8 66.0% 34.0% 57.4% 29.6% 37 17 37.0 17.0 68.5% 31.5% 68.5% 31.5%
Count Ex pec ted Count % within deck % of Total Count Ex pec ted Count % within deck % of Total Count Ex pec ted Count % within deck % of Total
Total 7 7.0 100.0% 13.0% 47 47.0 100.0% 87.0% 54 54.0 100.0% 100.0%
Chi-Square Tests
Pearson Chi-Square Continuity Correction a Likelihood Ratio Fis her's Exact Test Linear-by-Linear As soci ation N of Valid Cases
Value 1.102 b .377 1.248
df 1 1 1
As ymp. Sig. (2-sided) .294 .539 .264
Exact Sig. (2-sided)
.412 1.082
Exact Sig. (1-sided)
.281
.298
1
54
a. Computed only for a 2x2 table b. 2 cells (50.0%) have expected count less than 5. The mi nimum expected count is 2. 20. Ris k Es tima te
Va lue Od ds Ratio for d eck (re siko / tida k ad a res iko) Fo r coh ort keberadaa n vektor = ada Fo r coh ort keberadaa n vektor = tida k ad a N o f Va lid Cases
95 % Co nfid ence Interval Lo wer Up per
3.0 97
.34 3
27 .985
1.3 00
.90 2
1.8 73
.42 0
.06 5
2.6 89
54
Universitas Sumatera Utara
kamar awak kapal * keberadaan vektor Crosstab
kamar awak kapal
res iko
Count Ex pec ted Count % within kamar awak k apal % of Total Count Ex pec ted Count % within kamar awak k apal % of Total Count Ex pec ted Count % within kamar awak k apal % of Total
tidak ada resik o
Total
keberadaan vek tor ada tidak ada 30 8 12.0 26.0
Total 38 38.0
78.9%
21.1%
100.0%
55.6% 7 11.0
14.8% 9 5.0
70.4% 16 16.0
43.8%
56.3%
100.0%
13.0% 37 37.0
16.7% 17 17.0
29.6% 54 54.0
68.5%
31.5%
100.0%
68.5%
31.5%
100.0%
Chi-Square Tests
Pearson Chi-Square Continuity Correction a Likelihood Ratio Fis her's Exact Test Linear-by-Linear As sociation N of Valid Cases
Value 6.466b 4.938 6.229
6.347
As ymp. Sig. (2-sided) .011 .026 .013
df 1 1 1
1
Exact Sig. (2-sided)
Exact Sig. (1-sided)
.022
.014
.012
54
a. Computed only for a 2x2 table b. 0 cells (.0%) have expected count less than 5. The m inim um expected count is 5. 04. Ris k Es timate
Va lue Od ds Ratio for kama r awak kapa l (res iko / tid ak a da re siko ) Fo r coh ort kebe rada an ve ktor = ad a Fo r coh ort kebe rada an ve ktor = tida k ad a N of Va lid Case s
95 % Confid ence Interva l Lo wer Up per
4.8 21
1.3 70
16 .972
1.8 05
1.0 11
3.2 21
.37 4
.17 6
.79 4
54
Universitas Sumatera Utara
toilet * keberadaan vektor Crosstab
toi let
res iko
tidak ada resiko
Total
keberadaan vektor ada tidak ada 5 30 11.0 24.0 14.3% 85.7% 9.3% 55.6% 7 12 13.0 6.0 63.2% 36.8% 22.2% 13.0% 17 37 37.0 17.0 31.5% 68.5% 31.5% 68.5%
Count Expected Count % within toilet % of Total Count Expected Count % within toilet % of Total Count Expected Count % within toilet % of Total
Total 35 35.0 100.0% 64.8% 19 19.0 100.0% 35.2% 54 54.0 100.0% 100.0%
Chi-Square Tests
Pearson Chi-Square Continuity Correction a Likelihood Ratio Fis her's Exact Test Linear-by-Linear As sociation N of Valid Cases
Value 13.636 b 11.464 13.557
13.384
As ymp. Sig. (2-sided) .000 .001 .000
df 1 1 1
1
Exact Sig. (2-sided)
Exact Sig. (1-sided)
.000
.000
.000
54
a. Computed only for a 2x2 table b. 0 cells (.0%) have expected count less than 5. The minimum expected count is 5. 98.
Risk Estimate
Value Odds Ratio for toilet (resiko / tidak ada res iko) For cohort keberadaan vektor = ada For cohort keberadaan vektor = tidak ada N of Valid Cases
95% Confidence Interval Lower Upper
10.286
2.724
38.837
2.327
1.272
4.256
.226
.094
.546
54
Universitas Sumatera Utara
dapur * keberadaan vektor Crosstab
dapur
res iko
tidak ada resiko
Total
keberadaan vektor tidak ada ada 28 4 21.9 10.1 87.5% 12.5% 7.4% 51.9% 9 13 15.1 6.9 40.9% 59.1% 24.1% 16.7% 37 17 37.0 17.0 68.5% 31.5% 68.5% 31.5%
Count Expected Count % within dapur % of Total Count Expected Count % within dapur % of Total Count Expected Count % within dapur % of Total
Total 32 32.0 100.0% 59.3% 22 22.0 100.0% 40.7% 54 54.0 100.0% 100.0%
Chi-Square Tests
Pearson Chi-Square Continuity Correction a Likelihood Ratio Fis her's Exact Test Linear-by-Linear As sociation N of Valid Cases
Value 13.120 b 11.049 13.393
12.877
df 1 1 1
As ymp. Sig. (2-sided) .000 .001 .000
1
Exact Sig. (2-sided)
Exact Sig. (1-sided)
.001
.000
.000
54
a. Computed only for a 2x2 table b. 0 cells (.0%) have expected count less than 5. The m inim um expected count is 6. 93.
Risk Estimate
Value Odds Ratio for dapur (resiko / tidak ada res iko) For cohort keberadaan vektor = ada For cohort keberadaan vektor = tidak ada N of Valid Cases
95% Confidence Interval Lower Upper
10.111
2.624
38.965
2.139
1.273
3.594
.212
.079
.564
54
Universitas Sumatera Utara
gudang persediaan makanan * keberadaan vektor Crosstab
gudang persediaan makanan
res iko
tidak ada resik o
Total
Count Ex pec ted Count % within gudang persediaan makanan % of Total Count Ex pec ted Count % within gudang persediaan makanan % of Total Count Ex pec ted Count % within gudang persediaan makanan % of Total
keberadaan vek tor ada tidak ada 29 8 11.6 25.4
Total 37 37.0
78.4%
21.6%
100.0%
53.7% 8 11.6
14.8% 9 5.4
68.5% 17 17.0
47.1%
52.9%
100.0%
14.8% 37 37.0
16.7% 17 17.0
31.5% 54 54.0
68.5%
31.5%
100.0%
68.5%
31.5%
100.0%
Chi-Square Tests
Pearson Chi-Square Continuity Correction a Likelihood Ratio Fis her's Exact Test Linear-by-Linear As soci ation N of Valid Cases
Value 5.297b 3.944 5.131
5.199
df 1 1 1
As ymp. Sig. (2-sided) .021 .047 .023
1
Exact Sig. (2-sided)
Exact Sig. (1-sided)
.030
.025
.023
54
a. Computed only for a 2x2 table b. 0 cells (.0%) have expected count less than 5. The m inim um expected count is 5. 35.
Risk Estimate
Value Odds Ratio for gudang persediaan makanan (resiko / tidak ada res iko) For cohort keberadaan vektor = ada For cohort keberadaan vektor = tidak ada N of Valid Cases
95% Confidence Interval Lower Upper
4.078
1.189
13.991
1.666
.979
2.835
.408
.191
.873
54
Universitas Sumatera Utara
Logistic Regression Case Processing Summary Unweighted Cases Selected Cases
a
N Included in Anal ysis Mis sing Cases Total
54 0 54 0 54
Unselected Cas es Total
Percent 100.0 .0 100.0 .0 100.0
a. If weight is in effect, s ee class ification table for the total number of cases.
De pe n de n t V a ria ble Or igina l Va lue ad a tid ak a da
Enc odi ng
Int erna l Va lue 0 1
Block 0: Beginning Block Classification Table a,b Predicted
Step 0
Observed keberadaan vektor
keberadaan vektor ada tidak ada 37 0 17 0
ada tidak ada
Overall Percentage
Percentage Correct 100.0 .0 68.5
a. Constant is included in the model. b. The cut value is .500
Va riables in the Equa tion
St ep 0
Constant
B -.778
S. E. .293
W ald 7.045
df 1
Sig. .008
Ex p(B) .459
Universitas Sumatera Utara
Va riables not in the Equa tion St ep 0
Variables Overall Statistic s
df
Sc ore 1.102 1.102
deck
1 1
Sig. .294 .294
Block 1: Method = Enter Omnibus Tests of Model Coefficients Step 1
Chi-square 1.248 1.248 1.248
Step Block Model
df
Sig. .264 .264 .264
1 1 1
Model Summar y -2 Log likelihood 66.025 a
Step 1
Cox & Snel l R Square .023
Nagelkerke R Square .032
a. Es timation term inated at iteration num ber 5 because param eter estim ates changed by les s than .001.
Classification Table a Predicted
Step 1
Observed keberadaan vektor
keberadaan vektor ada tidak ada 37 0 17 0
ada tidak ada
Overall Percentage
Percentage Correct 100.0 .0 68.5
a. The cut value is .500
Variables in the Equation
Step a 1
deck Constant
B 1.130 -2.922
S.E. 1.123 2.182
Wald 1.013 1.793
df 1 1
Sig. .314 .181
Exp(B) 3.097 .054
95.0% C.I.for EXP(B) Upper Lower .343 27.985
a. Variable(s) entered on step 1: deck.
Universitas Sumatera Utara
Logistic Regression Case Processing Summary Unweighted Cases Selected Cases
a
N Included in Anal ysis Mis sing Cases Total
54 0 54 0 54
Unselected Cas es Total
Percent 100.0 .0 100.0 .0 100.0
a. If weight is in effect, s ee class ification table for the total number of cases.
De pe n de n t V a ria ble Or igina l Va lue ad a tid ak a da
Enc odi ng
Int erna l Va lue 0 1
Block 0: Beginning Block Classification Table a,b Predicted
Step 0
Observed keberadaan vektor
keberadaan vektor ada tidak ada 37 0 0 17
ada tidak ada
Overall Percentage
Percentage Correct 100.0 .0 68.5
a. Constant is included in the model. b. The cut value is .500
Va riables in the Equa tion
St ep 0
Constant
B -.778
S. E. .293
W ald 7.045
df 1
Sig. .008
Ex p(B) .459
Universitas Sumatera Utara
Va riables not in the Equa tion St ep 0
Variables Overall Statistic s
df
Sc ore 6.466 6.466
ktotk
1 1
Sig. .011 .011
Block 1: Method = Enter Omnibus Tests of Model Coefficients Step 1
Chi-square 6.229 6.229 6.229
Step Block Model
df
Sig. .013 .013 .013
1 1 1
Model Summar y -2 Log likelihood 61.044 a
Step 1
Cox & Snel l R Square .109
Nagelkerke R Square .153
a. Es timation term inated at iteration num ber 4 because param eter estim ates changed by les s than .001.
Classification Table a Predicted
Step 1
Observed keberadaan vektor
keberadaan vektor ada tidak ada 30 7 8 9
ada tidak ada
Overall Percentage
Percentage Correct 81.1 52.9 72.2
a. The cut value is .500
Variables in the Equation
Step a 1
ktotk Constant
B 1.573 -2.895
S.E. .642 .942
Wald 6.002 9.444
df 1 1
Sig. .014 .002
Exp(B) 4.821 .055
95.0% C.I.for EXP(B) Lower Upper 1.370 16.972
a. Variable(s) entered on step 1: ktotk.
Universitas Sumatera Utara
Logistic Regression Case Processing Summary Unweighted Cases Selected Cases
a
N Included in Anal ysis Mis sing Cases Total
54 0 54 0 54
Unselected Cas es Total
Percent 100.0 .0 100.0 .0 100.0
a. If weight is in effect, s ee class ification table for the total number of cases.
De pe n de n t V a ria ble Or igina l Va lue ad a tid ak a da
Enc odi ng
Int erna l Va lue 0 1
Block 0: Beginning Block Classification Table a,b Predicted
Step 0
Observed keberadaan vektor
keberadaan vektor ada tidak ada 37 0 0 17
ada tidak ada
Overall Percentage
Percentage Correct 100.0 .0 68.5
a. Constant is included in the model. b. The cut value is .500
Va riables in the Equa tion
St ep 0
Constant
B -.778
S. E. .293
W ald 7.045
df 1
Sig. .008
Ex p(B) .459
Universitas Sumatera Utara
Va riables not in the Equa tion St ep 0
Variables Overall Statistic s
df
Sc ore 13.636 13.636
kmtot
1 1
Sig. .000 .000
Block 1: Method = Enter Omnibus Tests of Model Coefficients Step 1
Chi-square 13.557 13.557 13.557
Step Block Model
df
Sig. .000 .000 .000
1 1 1
Model Summar y -2 Log likelihood 53.716 a
Step 1
Cox & Snel l R Square .222
Nagelkerke R Square .312
a. Es timation term inated at iteration num ber 5 because param eter estim ates changed by les s than .001.
Classification Table a Predicted
Step 1
Observed keberadaan vektor
keberadaan vektor ada tidak ada 30 7 5 12
ada tidak ada
Overall Percentage
Percentage Correct 81.1 70.6 77.8
a. The cut value is .500
Variables in the Equation
Step a 1
kmtot Constant
B 2.331 -4.123
S.E. .678 1.077
Wald 11.822 14.657
df 1 1
Sig. .001 .000
Exp(B) 10.286 .016
95.0% C.I.for EXP(B) Lower Upper 2.724 38.837
a. Variable(s) entered on step 1: kmtot.
Universitas Sumatera Utara
Logistic Regression Case Processing Summary Unweighted Cases Selected Cases
a
N Included in Anal ysis Mis sing Cases Total
54 0 54 0 54
Unselected Cas es Total
Percent 100.0 .0 100.0 .0 100.0
a. If weight is in effect, s ee class ification table for the total number of cases.
De pe n de n t V a ria ble Or igina l Va lue ad a tid ak a da
Enc odi ng
Int erna l Va lue 0 1
Block 0: Beginning Block Classification Table a,b Predicted
Step 0
Observed keberadaan vektor
keberadaan vektor tidak ada ada 37 0 0 17
ada tidak ada
Overall Percentage
Percentage Correct 100.0 .0 68.5
a. Constant is included in the model. b. The cut value is .500
Va riables in the Equa tion
St ep 0
Constant
B -.778
S. E. .293
W ald 7.045
df 1
Sig. .008
Ex p(B) .459
Universitas Sumatera Utara
Va riables not in the Equa tion St ep 0
Variables Overall Statistic s
df
Sc ore 13.120 13.120
datotk
1 1
Sig. .000 .000
Block 1: Method = Enter Omnibus Tests of Model Coefficients Step 1
Chi-square 13.393 13.393 13.393
Step Block Model
df
Sig. .000 .000 .000
1 1 1
Model Summar y -2 Log likelihood 53.880 a
Step 1
Cox & Snel l R Square .220
Nagelkerke R Square .308
a. Es timation term inated at iteration num ber 5 because param eter estim ates changed by les s than .001.
Classification Table a Predicted
Step 1
Observed keberadaan vektor
keberadaan vektor ada tidak ada 28 9 4 13
ada tidak ada
Overall Percentage
Percentage Correct 75.7 76.5 75.9
a. The cut value is .500 Variables in the Equation
Step a 1
datotk Constant
B 2.314 -4.260
S.E. .688 1.154
Wald 11.299 13.633
df 1 1
Sig. .001 .000
Exp(B) 10.111 .014
95.0% C.I.for EXP(B) Lower Upper 2.624 38.965
a. Variable(s) entered on step 1: datotk.
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Logistic Regression Case Processing Summary Unweighted Cases Selected Cases
a
N Included in Anal ysis Mis sing Cases Total
54 0 54 0 54
Unselected Cas es Total
Percent 100.0 .0 100.0 .0 100.0
a. If weight is in effect, s ee class ification table for the total number of cases.
De pe n de n t V a ria ble Or igina l Va lue ad a tid ak a da
Enc odi ng
Int erna l Va lue 0 1
Block 0: Beginning Block Classification Table a,b Predicted
Step 0
Observed keberadaan vektor
keberadaan vektor ada tidak ada 37 0 0 17
ada tidak ada
Overall Percentage
Percentage Correct 100.0 .0 68.5
a. Constant is included in the model. b. The cut value is .500
Va riables in the Equa tion
St ep 0
Constant
B -.778
S. E. .293
W ald 7.045
df 1
Sig. .008
Ex p(B) .459
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Va riables not in the Equa tion St ep 0
Variables Overall Statistic s
df
Sc ore 5.297 5.297
gtotk
1 1
Sig. .021 .021
Block 1: Method = Enter Omnibus Tests of Model Coefficients Step 1
Chi-square 5.131 5.131 5.131
Step Block Model
df
Sig. .023 .023 .023
1 1 1
Model Summar y -2 Log likelihood 62.142 a
Step 1
Cox & Snel l R Square .091
Nagelkerke R Square .127
a. Es timation term inated at iteration num ber 4 because param eter estim ates changed by les s than .001.
Classification Table a Predicted
Step 1
Observed keberadaan vektor
keberadaan vektor ada tidak ada 29 8 8 9
ada tidak ada
Overall Percentage
Percentage Correct 78.4 52.9 70.4
a. The cut value is .500 Variables in the Equation
Step a 1
gtotk Constant
B 1.406 -2.693
S.E. .629 .935
Wald 4.995 8.300
df 1 1
Sig. .025 .004
Exp(B) 4.078 .068
95.0% C.I.for EXP(B) Lower Upper 1.189 13.991
a. Variable(s) entered on step 1: gtotk.
Universitas Sumatera Utara
Logistic Regression Case Processing Summary Unweighted Cases Selected Cases
a
N Included in Anal ysis Mis sing Cases Total
54 0 54 0 54
Unselected Cas es Total
Percent 100.0 .0 100.0 .0 100.0
a. If weight is in effect, s ee class ification table for the total number of cases.
De pe n de n t V a ria ble Or igina l Va lue ad a tid ak a da
Enc odi ng
Int erna l Va lue 0 1
Block 0: Beginning Block Classification Table a,b Predicted
Step 0
Observed keberadaan vektor
keberadaan vektor tidak ada ada 37 0 0 17
ada tidak ada
Overall Percentage
Percentage Correct 100.0 .0 68.5
a. Constant is included in the model. b. The cut value is .500
Va riables in the Equa tion
St ep 0
Constant
B -.778
S. E. .293
W ald 7.045
df 1
Sig. .008
Ex p(B) .459
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Va riables not in the Equa tion St ep 0
Variables
Sc ore 6.466 13.636 13.120 5.297 21.556
ktotk kmtot datotk gtotk
Overall Statistics
df 1 1 1 1 4
Sig. .011 .000 .000 .021 .000
Block 1: Method = Enter Omnibus Tests of Model Coefficients Step 1
Chi-square 24.286 24.286 24.286
Step Block Model
df
Sig. .000 .000 .000
4 4 4
Model Summar y -2 Log likelihood 42.987 a
Step 1
Cox & Snel l R Square .362
Nagelkerke R Square .509
a. Es timation term inated at iteration num ber 6 because param eter estim ates changed by les s than .001. Classification Table
a
Predicted
Step 1
Observed keberadaan vektor
keberadaan vektor ada tidak ada 36 1 7 10
ada tidak ada
Overall Percentage
Percentage Correct 97.3 58.8 85.2
a. The cut value is .500
Variables in the Equation
Step a 1
ktotk kmtot datotk gtotk Constant
B 1.229 1.538 1.677 1.466 -9.206
S.E. .795 .801 .847 .833 2.501
Wald 2.392 3.683 3.923 3.097 13.544
df 1 1 1 1 1
Sig. .122 .055 .048 .078 .000
Exp(B) 3.418 4.655 5.348 4.330 .000
95.0% C.I.for EXP(B) Lower Upper .720 16.228 .968 22.387 1.018 28.108 .846 22.153
a. Variable(s) entered on step 1: ktotk, kmtot, datotk, gtotk.
Universitas Sumatera Utara
Logistic Regression Case Processing Summary Unweighted Cases Selected Cases
a
N Included in Anal ysis Mis sing Cases Total
54 0 54 0 54
Unselected Cas es Total
Percent 100.0 .0 100.0 .0 100.0
a. If weight is in effect, s ee class ification table for the total number of cases.
De pe n de n t V a ria ble Or igina l Va lue ad a tid ak a da
Enc odi ng
Int erna l Va lue 0 1
Block 0: Beginning Block Classification Table a,b Predicted
Step 0
Observed keberadaan vektor
keberadaan vektor tidak ada ada 37 0 17 0
ada tidak ada
Overall Percentage
Percentage Correct 100.0 .0 68.5
a. Constant is included in the model. b. The cut value is .500
Va riables in the Equa tion
St ep 0
Constant
B -.778
S. E. .293
W ald 7.045
df 1
Sig. .008
Ex p(B) .459
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Variables not in the Equation Step 0
Variables
Score 13.636 13.120 5.297 20.192
kmtot datotk gtotk
Overall Statistics
df 1 1 1 3
Sig. .000 .000 .021 .000
Block 1: Method = Enter Omnibus Tests of Model Coefficients Step 1
Chi-square 21.827 21.827 21.827
Step Block Model
df
Sig. .000 .000 .000
3 3 3
Model Summar y -2 Log likelihood 45.446 a
Step 1
Cox & Snel l R Square .332
Nagelkerke R Square .467
a. Es timation term inated at iteration num ber 5 because param eter estim ates changed by les s than .001.
Classification Table a Predicted
Step 1
Observed keberadaan vektor
keberadaan vektor ada tidak ada 33 4 6 11
ada tidak ada
Overall Percentage
Percentage Correct 89.2 64.7 81.5
a. The cut value is .500
Va riables in the Equa tion
Step a 1
kmtot datotk gtotk Constant
B 1.434 1.905 1.390 -7.574
S.E. .783 .819 .809 1.993
W ald 3.351 5.414 2.948 14.437
df 1 1 1 1
Sig. .067 .020 .086 .000
Ex p(B) 4.194 6.721 4.014 .001
95.0% C.I.for EXP(B) Lower Upper .904 19.463 1.350 33.453 .821 19.612
a. Variable(s) entered on step 1: k mtot, datotk , gtotk.
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Logistic Regression Case Processing Summary Unweighted Cases Selected Cases
a
N Included in Anal ysis Mis sing Cases Total
54 0 54 0 54
Unselected Cas es Total
Percent 100.0 .0 100.0 .0 100.0
a. If weight is in effect, s ee class ification table for the total number of cases.
De pe n de n t V a ria ble Or igina l Va lue ad a tid ak a da
Enc odi ng
Int erna l Va lue 0 1
Block 0: Beginning Block Classification Table a,b Predicted
Step 0
Observed keberadaan vektor
keberadaan vektor ada tidak ada 37 0 0 17
ada tidak ada
Overall Percentage
Percentage Correct 100.0 .0 68.5
a. Constant is included in the model. b. The cut value is .500
Va riables in the Equa tion
St ep 0
Constant
B -.778
S. E. .293
W ald 7.045
df 1
Sig. .008
Ex p(B) .459
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Variables not in the Equation Step 0
Variables
Score 13.636 13.120 17.912
kmtot datotk
Overall Statistics
df 1 1 2
Sig. .000 .000 .000
Block 1: Method = Enter Omnibus Tests of Model Coefficients Step 1
Chi-square 18.735 18.735 18.735
Step Block Model
df
Sig. .000 .000 .000
2 2 2
Model Summar y -2 Log likelihood 48.538 a
Step 1
Cox & Snel l R Square .293
Nagelkerke R Square .412
a. Es timation term inated at iteration num ber 5 because param eter estim ates changed by les s than .001.
Classification Table a Predicted
Step 1
Observed keberadaan vektor
keberadaan vektor ada tidak ada 33 4 7 10
ada tidak ada
Overall Percentage
Percentage Correct 89.2 58.8 79.6
a. The cut value is .500 Variables in the Equation
Step a 1
kmtot datotk Constant
B 1.703 1.694 -5.768
S.E. .743 .754 1.455
Wald 5.251 5.052 15.713
df 1 1 1
Sig. .022 .025 .000
Exp(B) 5.492 5.441 .003
95.0% C.I.for EXP(B) Lower Upper 1.279 23.573 1.242 23.831
a. Variable(s) entered on step 1: kmtot, datotk.
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