Lampiran 1 LEMBA OBSEVASI PENGUMPULAN DATA PENGAUH FAKTO ISIKO TEHADAP KEBEADAAN VEKTO PENYAKIT DI KAPAL PADA PELABUHAN TEMBILAHAN Nama Kapal : Besar Kapal : Bendera : Tanggal SSCEC : Jenis Kapal : A. DECK No Komponen yang dinilai 1 Kebersihan (Tidak ada sampah, oli ) 2 Lantai kedap air, genangan air 3 Lantai tidak berkarat 4 Lantai rata, sambungan tidak menonjol 5 Barang-barang APD, tali tersusun rapi Nilai Tdk baik Baik (0) (1) Keberadaan Vektor.Ada T.Ada (1) (2) B. KAMA AWAK KAPAL No Komponen yang dinilai 1 Kebersihan ( 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 Nilai Tdk baik Baik (0) (1) Keberadaan Vektor.Ada T.Ada (1) (2)
C. KAMA MANDI/TOILET No Komponen yang dinilai 1 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 Nilai Tdk baik Baik (0) (1) Keberadaan Vektor.Ada T.Ada (1) (2) D. DAPU No Komponen yang dinilai 1 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 Nilai Tdk baik Baik (0) (1) Keberadaan Vektor.Ada T.Ada (1) (2)
E. GUDANG PESEDIAAN MAKANAN No Komponen yang dinilai 1 Kebersihan (Tidak ada 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 makanan tidak mudah membusuk disimpan 10-15 derajat Celcius Nilai Tdk baik Baik (0) (1) Keberadaan Vektor.Ada T.Ada (1) (2)
Lampiran 2 Dokumentasi Hasil Penelitian Gambar 1: Dapur Kapal Gambar 2: Dapur kapal
Gambar 3: Deck Kapal Gambar 4: Gudang Persediaan Makanan di Kapal
Gambar 5: Gudang Persediaan Makanan di Kapal Gambar 6: Toilet di Kapal
Gambar 7: Toilet di Kapal Gambar 8: Kapal Kargo Motor Venture
Gambar 9: Dapur di Kapal Gambar 10: Toilet di Kapal
Gambar 11: Toilet di Kapal Gambar 12: Gudang Persediaan Makanan
Gambar 13: Kamar Awak kapal Gambar 14: Deck Kapal
Gambar 15: Kapal Tug Boat
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 (M3) Bendera Datang dari 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.ajawali 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
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
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
Lampiran 4 HASIL OBSEVASI PENGAUH FAKTO ISIKO TEHADAP KEBEADAAN VEKTO DI KAPAL K DECK pl No komponen Vektor kategori nilai KM AWAK KAPAL No Komponen nilai Kategori Vektor FAKTO ISIKO DI KAPAL KAMA MANDI/TOILET DAPU No Komponen nilai Kategori Vektor No Komponen Vektor Kategori nilai GUD PES MAKANAN No Komponen 1 2 3 4 5 1 2 3 4 1 2 3 4 5 6 7 1 2 3 4 5 6 7 8 1 2 3 4 5 6 7 Vektor kategori nilai Nilai Nilai Nilai Nilai Nilai 1 0 0 0 1 0 1 A Ad 0 0 1 0 1 A Ad 1 1 1 0 0 0 1 4 T Ta 0 0 0 1 1 1 0 0 3 A Ad 0 1 1 1 0 1 1 5 T Ta 2 0 0 0 0 0 0 A Ta 1 1 1 0 3 T Ta 1 1 1 0 1 0 0 4 T Ta 1 0 0 1 1 1 1 0 5 T Ad 0 1 1 1 1 0 0 4 T Ad 3 0 0 0 1 0 1 A Ta 1 1 1 0 3 T 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 A Ad 4 0 0 0 1 0 1 A Ta 1 1 1 1 4 T Ta 0 1 1 0 0 0 1 3 A Ta 1 0 1 1 1 1 1 1 7 T Ta 1 0 1 1 1 1 1 6 T Ta 5 1 1 1 1 0 4 T Ta 1 1 1 0 3 T Ta 0 1 1 1 0 0 1 4 T Ad 1 0 0 1 1 1 0 1 5 T Ad 1 0 1 1 0 1 1 5 T 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 T Ad 0 1 0 1 0 0 0 2 Ar Ad 7 0 0 0 1 0 1 A Ta 0 0 1 0 1 A Ad 0 0 0 0 0 0 1 1 A Ad 0 0 0 1 1 1 1 1 5 T Ta 1 1 1 1 0 1 0 5 T Ad 8 1 1 0 1 0 3 T Ta 0 1 1 1 3 T Ad 0 0 0 0 0 0 1 1 A Ad 0 0 1 1 1 1 1 0 5 T Ta 1 1 1 1 1 1 0 6 T Ta 9 0 0 0 1 0 1 A Ta 0 0 1 0 1 A Ad 0 1 1 1 1 0 1 5 T Ad 0 0 0 1 1 1 0 0 3 A Ad 0 0 0 1 0 0 0 1 A Ad
10 1 1 1 0 1 4 T Ad 1 1 1 0 3 T Ta 0 0 1 0 0 0 0 1 A Ad 1 0 1 1 1 1 1 0 6 T Ad 1 1 1 1 1 1 0 6 T Ta 11 1 1 1 0 1 4 T Ta 0 0 1 0 1 A Ad 0 0 1 0 0 0 1 2 A Ad 1 0 0 1 1 1 1 1 5 T Ad 1 1 1 1 1 0 0 5 T Ta 12 1 1 0 1 1 4 T Ta 0 0 1 0 1 A Ad 0 1 1 1 0 0 1 4 T Ta 0 0 0 1 1 0 0 0 2 A Ad 0 1 0 1 0 0 0 2 A Ad 13 0 1 1 1 1 4 T Ad 0 0 1 0 1 A Ta 0 0 1 0 0 0 1 2 A Ad 0 1 0 1 1 1 1 0 5 T Ad 1 1 0 1 0 1 1 5 T Ad 14 0 1 1 1 1 4 T Ad 1 1 1 0 3 T Ad 0 0 1 0 0 0 1 2 A Ta 0 0 0 1 1 1 0 0 3 A Ta 0 1 0 0 1 1 1 4 T Ad 15 0 1 1 1 1 4 T Ta 1 1 1 0 3 T Ta 0 0 1 0 0 0 1 2 A Ad 0 0 1 1 1 1 1 1 6 T Ad 1 1 1 1 1 1 0 6 T Ta K pl
FAKTO ISIKO DI KAPAL DECK No Komponen nilai Kategori Vektor KM AWAK KAPAL No Komponen nilai Kategori Vektor KAMA MANDI/TOILET No Komponen nilai Kategori Vektor DAPU No Komponen nilai Kategori Vektor GUD PES MAKANAN No Komponen nilai Kategori Vektor 1 2 3 4 5 1 2 3 4 1 2 3 4 5 6 7 1 2 3 4 5 6 7 8 1 2 3 4 5 6 7 Nilai Nilai Nilai Nilai Nilai 16 0 1 1 1 1 4 T Ta 0 0 1 0 1 A Ad 0 0 1 0 0 0 1 2 A Ad 0 0 0 1 1 0 0 1 3 A Ad 0 1 1 1 0 0 0 3 A Ta 17 1 1 1 1 1 5 T Ta 0 0 0 0 0 A Ad 0 0 0 0 0 0 1 1 A Ad 0 0 0 1 1 0 0 0 2 A Ad 0 1 0 0 0 0 0 1 A Ad 18 1 0 1 1 1 4 T Ta 0 1 1 1 3 T Ad 0 1 1 1 1 0 1 5 T Ad 0 0 0 1 0 1 0 1 3 A Ad 0 0 1 1 0 0 0 2 A Ad 19 1 1 0 1 0 3 T Ta 1 1 0 1 3 T Ta 0 1 1 1 1 1 1 6 T Ta 1 1 0 1 1 1 1 0 6 T Ta 0 1 0 1 0 0 0 2 A Ad 20 1 0 1 1 1 4 T 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 A Ad 1 1 1 1 0 1 0 5 T Ad 21 1 1 0 1 1 4 T Ta 0 0 1 0 1 A Ta 0 0 1 0 0 0 0 1 A Ta 0 0 0 1 1 1 0 0 3 A Ta 1 1 0 0 0 0 0 2 A Ad 22 0 1 1 1 1 4 T Ta 1 1 1 1 4 T Ta 0 0 1 0 0 0 1 2 A Ta 1 0 1 1 1 1 1 1 7 T Ta 0 0 0 0 0 0 0 0 A Ta 23 0 1 1 1 0 3 T Ta 0 0 1 0 1 A Ta 1 1 1 1 1 0 1 6 T Ta 0 0 0 1 1 1 0 0 3 A Ta 1 1 0 1 0 0 0 3 A Ad 24 0 1 1 1 1 4 T Ad 1 0 0 0 1 A Ta 0 0 1 0 0 0 1 2 A Ta 0 0 0 1 0 1 1 0 3 A Ad 0 0 0 0 1 1 1 3 A Ad 25 1 1 0 0 1 3 T Ad 0 0 1 0 1 A Ad 0 0 0 0 0 0 1 1 A Ad 0 0 0 1 1 0 1 0 3 A Ta 0 1 0 0 1 1 0 2 A Ad 26 1 0 1 0 1 3 T Ad 0 0 1 0 1 A Ad 0 0 1 0 0 0 1 2 A Ad 0 0 0 1 1 1 0 0 3 A Ad 0 1 0 0 0 1 0 2 A Ad 27 0 1 1 1 0 3 T Ta 0 0 1 0 1 A Ad 0 0 1 0 1 0 1 3 A Ad 1 0 1 1 1 1 0 1 6 T Ta 0 0 0 1 1 0 1 3 A Ad
28 1 0 1 0 1 3 T Ad 0 0 1 0 1 A Ad 1 1 1 0 1 0 1 5 T Ad 0 0 0 1 1 1 0 0 3 A Ad 0 1 1 0 0 0 0 2 A Ad 29 1 1 0 1 0 3 T Ta 0 1 0 0 1 A Ad 0 0 1 0 0 0 1 2 A Ad 0 0 0 1 0 0 1 1 3 A Ad 0 0 0 1 0 0 0 1 A Ad 30 0 1 1 1 0 3 T Ad 0 1 1 1 3 T Ad 0 0 1 0 1 0 1 3 A Ad 0 0 0 0 1 1 0 0 2 A Ad 1 1 0 0 0 0 0 2 A Ad
DECK Kp No Komponen l Vektor Kategori nilai KM AWAK KAPAL No Komponen Vektor Kategori nilai FAKTO ISIKO DI KAPAL KAMA MANDI/TOILET DAPU No Komponen nilai Kategori Vektor No Komponen Vektor Kategori nilai GUD PES MAKANAN No Komponen 1 2 3 4 5 1 2 3 4 1 2 3 4 5 6 7 1 2 3 4 5 6 7 8 1 2 3 4 5 6 7 Vektor Kategori nilai Nilai Nilai Nilai Nilai Nilai 31 0 0 1 1 1 3 T Ta 1 0 1 1 3 T Ad 0 0 1 0 0 0 1 2 A Ad 1 0 0 1 1 1 1 0 5 T Ad 0 0 0 0 1 0 1 2 A Ta 32 1 0 1 1 1 4 T Ta 1 0 0 0 1 A Ta 0 0 1 0 0 0 1 2 A Ad 0 1 0 1 1 1 1 0 5 T Ta 0 0 0 0 0 0 1 6 A Ta 33 0 1 1 1 0 3 T Ta 0 0 1 0 1 A Ad 1 1 1 1 1 1 1 7 T Ad 1 1 0 1 1 1 0 0 5 T Ta 1 1 0 1 0 0 0 3 A Ta 34 1 1 0 1 0 3 T Ta 1 1 1 0 3 T Ad 0 0 0 0 0 0 1 6 A Ad 0 0 0 1 1 1 0 0 3 T Ad 0 0 0 0 0 0 0 0 A Ad 35 0 0 1 1 1 3 T Ta 0 0 1 0 1 A Ad 0 1 1 0 0 0 1 3 A Ad 0 0 1 1 1 1 1 0 5 T Ad 0 1 0 1 0 0 0 2 A Ad 36 1 1 1 1 0 4 T Ad 0 0 0 1 1 A Ta 0 0 1 0 0 0 1 2 A Ad 1 0 1 1 1 1 1 1 7 T Ta 0 0 0 0 0 0 0 0 A Ta 37 1 0 1 1 1 4 T Ta 0 0 1 0 1 A Ta 0 0 1 0 0 0 0 1 A Ad 0 0 0 1 1 1 0 0 3 A Ad 0 1 1 1 0 0 0 3 A Ta 38 0 1 1 1 1 4 T Ad 1 0 0 0 1 A Ta 0 1 1 0 0 0 0 2 A Ad 0 0 0 1 1 1 0 0 3 A Ad 1 1 0 0 0 0 0 2 A Ta 39 0 0 1 1 1 3 T Ta 0 0 0 1 1 A Ad 0 0 1 0 0 0 0 1 A Ad 0 0 0 1 1 1 0 0 3 A Ad 0 1 0 1 0 0 0 2 A Ad
40 1 1 1 1 0 4 T Ta 1 0 0 0 1 A Ad 1 1 1 1 1 1 1 7 T Ad 0 0 0 1 1 1 0 0 3 A Ad 1 1 0 0 0 0 0 2 A Ad 41 1 0 1 1 0 3 T Ad 1 0 0 0 1 A Ta 0 1 1 1 0 0 1 4 T Ad 0 0 0 1 1 1 0 0 3 A Ad 1 1 0 0 0 0 0 2 A Ad 42 0 1 0 1 1 3 T Ta 0 1 0 0 1 A Ad 1 0 1 0 0 0 0 2 A Ad 0 0 0 1 1 1 0 0 3 A Ad 0 1 1 0 0 0 0 2 A Ad 43 1 0 1 1 1 4 T Ta 1 0 0 0 1 A Ad 0 0 1 0 0 0 0 1 A Ad 1 0 1 1 1 1 1 0 5 T Ta 1 0 1 0 0 0 1 3 A Ad 44 1 1 0 1 0 3 T Ta 0 1 0 0 1 A Ad 0 1 1 1 0 0 0 3 A Ad 0 0 0 1 0 1 1 0 3 A Ad 0 1 0 1 0 0 0 2 A Ad 45 1 0 0 1 1 3 T Ta 0 1 0 1 3 T Ta 0 1 1 0 1 1 0 4 T Ad 0 1 1 0 0 0 0 1 3 A Ta 0 1 1 0 0 0 0 2 A Ad
DECK Kp No Komponen l Vektor Kategori nilai KM AWAK KAPAL No Komponen Vektor Kategori nilai FAKTO ISIKO DI KAPAL KAMA MANDI/TOILET DAPU No Komponen nilai Kategori Vektor No Komponen Vektor Kategori nilai GUD PES MAKANAN No Komponen 1 2 3 4 5 1 2 3 4 1 2 3 4 5 6 7 1 2 3 4 5 6 7 8 1 2 3 4 5 6 7 Vektor Kategori nilai Nilai Nilai Nilai Nilai Nilai 46 1 0 0 1 1 3 T Ad 0 0 1 0 1 A Ta 1 0 0 1 1 1 1 5 T Ta 0 1 1 1 0 1 0 1 5 T Ad 0 0 0 1 0 0 0 1 A Ta 47 1 0 0 1 1 3 T Ta 1 0 0 0 1 A Ta 1 0 0 0 1 1 1 4 T Ta 0 1 1 0 0 0 0 1 3 A Ta 0 0 0 0 1 0 1 2 A Ta 48 1 1 1 1 0 4 T Ad 0 0 1 0 1 A Ad 1 0 0 1 1 1 1 5 T Ta 0 0 0 1 1 1 0 0 3 A Ad 0 1 1 0 0 0 1 3 A Ad 49 1 1 0 1 0 3 T Ad 0 0 0 1 1 A Ad 1 0 0 1 1 1 1 5 T Ta 0 0 1 0 0 0 0 1 3 A Ta 0 0 0 1 0 0 0 1 A Ad 50 1 1 1 1 0 4 T Ad 0 0 1 0 1 A Ta 1 1 1 1 0 0 0 4 T Ta 0 0 1 0 0 0 1 1 3 A Ta 0 0 0 1 0 0 0 1 A Ad 51 1 1 1 0 1 4 T Ta 0 1 0 0 1 A Ta 1 1 1 1 1 1 1 7 T Ta 0 0 1 1 1 0 1 1 5 A Ad 1 1 0 0 0 0 0 2 A Ad 52 1 1 0 1 0 3 T Ad 0 1 0 0 1 A Ta 0 0 1 0 0 0 1 2 A Ad 1 1 0 1 1 1 1 0 6 T Ad 1 1 1 0 0 0 0 3 A Ad 53 0 0 1 1 1 3 T Ta 0 0 1 0 1 A Ad 0 1 1 1 1 0 1 5 T Ta 0 0 0 1 1 1 0 0 3 A Ta 0 1 0 1 0 0 0 2 A Ad 54 1 1 1 1 0 4 T Ta 0 0 1 0 1 A Ad 0 1 1 0 0 0 0 2 A Ad 0 1 1 0 0 0 0 0 2 A Ad 0 0 0 1 1 0 1 3 A Ad
Ket :- A (Ada isiko) - T (Tidak ada risiko) - Ad (Ada) - Ta (Tidak ada)
Frequencies Valid res iko resiko deck Cumulative Frequency Percent Valid Percent Percent 7 13.0 13.0 13.0 47 87.0 87.0 100.0 100.0 vektordeck Valid ada Cumulative Frequency Percent Valid Percent Percent 18 33.3 33.3 33.3 36 66.7 66.7 100.0 100.0 kamar awak kapal Valid res iko resiko Cumulative Frequency Percent Valid Percent Percent 38 70.4 70.4 70.4 16 29.6 29.6 100.0 100.0 vektorkamarawak Valid ada Cumulative Frequency Percent Valid Percent Percent 37 68.5 68.5 68.5 17 31.5 31.5 100.0 100.0 toilet Valid res iko resiko Cumulative Frequency Percent Valid Percent Percent 35 64.8 64.8 64.8 19 35.2 35.2 100.0 100.0
Valid ada vektoroilet Cumulative Frequency Percent Valid Percent Percent 35 64.8 64.8 64.8 19 35.2 35.2 100.0 100.0 dapur Valid res iko resiko Cumulative Frequency Percent Valid Percent Percent 32 59.3 59.3 59.3 22 40.7 40.7 100.0 100.0 vektordapur Valid ada Cumulative Frequency Percent Valid Percent Percent 40 74.1 74.1 74.1 14 25.9 25.9 100.0 100.0 gudang persediaan makanan Valid res iko resiko Cumulative Frequency Percent Valid Percent Percent 37 68.5 68.5 68.5 17 31.5 31.5 100.0 100.0 vektorgudang Valid ada Cumulative Frequency Percent Valid Percent Percent 38 70.4 70.4 70.4 16 29.6 29.6 100.0 100.0
Crosstabs deck * keberadaan vektor Crosstab deck res iko resiko Count Expected Count % within deck % of Count Expected Count % within deck % of Count Expected Count % within deck % of keberadaan vektor ada 6 1 7 4.8 2.2 7.0 85.7% 14.3% 100.0% 11.1% 1.9% 13.0% 31 16 47 32.2 14.8 47.0 66.0% 34.0% 100.0% 57.4% 29.6% 87.0% 37 17 54 37.0 17.0 54.0 68.5% 31.5% 100.0% 68.5% 31.5% 100.0% Chi-Square Tests Asymp. Sig. Value df (2-sided) Pearson Chi-Square 1.102 b 1.294 Continuity Correction a.377 1.539 Likelihood atio 1.248 1.264 Fis her's Exact Test Linear-by-Linear As sociation 1.082 1.298 N of Valid Cases 54 a. Computed only for a 2x2 table Exact Sig. (2-sided) Exact Sig. (1-sided).412.281 b. 2 cells (50.0%) have expected count less than 5. The minimum expected count is 2. 20. isk Estimate Odds atio for deck (resiko / resiko) For cohort keberadaan vektor = ada For cohort keberadaan vektor = N of Valid Cases 95% Confidence Interval Value Lower Upper 3.097.343 27.985 1.300.902 1.873.420.065 2.689 54
kamar awak kapal * keberadaan vektor Crosstab kamar awak kapal res iko resiko Count Expected Count % within kamar awak kapal % of Count Expected Count % within kamar awak kapal % of Count Expected Count % within kamar awak kapal % of keberadaan vek tor ada 30 8 38 26.0 12.0 38.0 78.9% 21.1% 100.0% 55.6% 14.8% 70.4% 7 9 16 11.0 5.0 16.0 43.8% 56.3% 100.0% 13.0% 16.7% 29.6% 37 17 54 37.0 17.0 54.0 68.5% 31.5% 100.0% 68.5% 31.5% 100.0% Chi-Square Tests Pearson Chi-Square Continuity Correction a Likelihood atio Fis her's Exact Test Linear-by-Linear As sociation N of Valid Cases Asymp. Sig. Value df (2-sided) 6.466 b 1.011 4.938 1.026 6.229 1.013 6.347 1.012 54 a. Computed only for a 2x2 table Exact Sig. (2-sided) Exact Sig. (1-sided).022.014 b. 0 cells (.0%) have expected count less than 5. The minimum expected count is 5. 04. isk Estimate Odds atio for kamar awak kapal (res iko / resiko) For cohort keberadaan vektor = ada For cohort keberadaan vektor = N of Valid Cases 95% Confidence Interval Value Lower Upper 4.821 1.370 16.972 1.805 1.011 3.221.374.176.794 54
toilet * keberadaan vektor Crosstab toilet res iko resiko Count Expected Count % within toilet % of Count Expected Count % within toilet % of Count Expected Count % within toilet % of keberadaan vektor ada 30 5 35 24.0 11.0 35.0 85.7% 14.3% 100.0% 55.6% 9.3% 64.8% 7 12 19 13.0 6.0 19.0 36.8% 63.2% 100.0% 13.0% 22.2% 35.2% 37 17 54 37.0 17.0 54.0 68.5% 31.5% 100.0% 68.5% 31.5% 100.0% Pearson Chi-Square Continuity Correction a Likelihood atio Fis her's Exact Test Linear-by-Linear As sociation N of Valid Cases Chi-Square Tests Asymp. Sig. Value df (2-sided) 13.636 b 1.000 11.464 1.001 13.557 1.000 13.384 1.000 54 a. Computed only for a 2x2 table Exact Sig. (2-sided) Exact Sig. (1-sided).000.000 b. 0 cells (.0%) have expected count less than 5. The minimum expected count is 5. 98. isk Estimate Odds atio for toilet (resiko / resiko) For cohort keberadaan vektor = ada For cohort keberadaan vektor = N of Valid Cases Value Lower Upper 10.286 2.724 38.837 2.327 1.272 4.256.226.094.546 54 95% Confidence Interval
dapur * keberadaan vektor Crosstab dapur res iko resiko Count Expected Count % within dapur % of Count Expected Count % within dapur % of Count Expected Count % within dapur % of keberadaan vektor ada 28 4 32 21.9 10.1 32.0 87.5% 12.5% 100.0% 51.9% 7.4% 59.3% 9 13 22 15.1 6.9 22.0 40.9% 59.1% 100.0% 16.7% 24.1% 40.7% 37 17 54 37.0 17.0 54.0 68.5% 31.5% 100.0% 68.5% 31.5% 100.0% Pearson Chi-Square Continuity Correction a Likelihood atio Fis her's Exact Test Linear-by-Linear As sociation N of Valid Cases Chi-Square Tests Asymp. Sig. Value df (2-sided) 13.120 b 1.000 11.049 1.001 13.393 1.000 12.877 1.000 54 a. Computed only for a 2x2 table Exact Sig. (2-sided) Exact Sig. (1-sided).001.000 b. 0 cells (.0%) have expected count less than 5. The minimum expected count is 6. 93. isk Estimate Odds atio for dapur (resiko / resiko) For cohort keberadaan vektor = ada For cohort keberadaan vektor = N of Valid Cases Value Lower Upper 10.111 2.624 38.965 2.139 1.273 3.594.212.079.564 54 95% Confidence Interval
gudang persediaan makanan * keberadaan vektor Crosstab gudang persediaan makanan res iko resiko Count Expected Count % within gudang persediaan makanan % of Count Expected Count % within gudang persediaan makanan % of Count Expected Count % within gudang persediaan makanan % of keberadaan vektor ada 29 8 37 25.4 11.6 37.0 78.4% 21.6% 100.0% 53.7% 14.8% 68.5% 8 9 17 11.6 5.4 17.0 47.1% 52.9% 100.0% 14.8% 16.7% 31.5% 37 17 54 37.0 17.0 54.0 68.5% 31.5% 100.0% 68.5% 31.5% 100.0% Chi-Square Tests Pearson Chi-Square Continuity Correction a Likelihood atio Fis her's Exact Test Linear-by-Linear As sociation N of Valid Cases Asymp. Sig. Value df (2-sided) 5.297 b 1.021 3.944 1.047 5.131 1.023 5.199 1.023 54 a. Computed only for a 2x2 table Exact Sig. (2-sided) Exact Sig. (1-sided).030.025 b. 0 cells (.0%) have expected count less than 5. The minimum expected count is 5. 35. isk Estimate Odds atio for gudang persediaan makanan (resiko / resiko) For cohort keberadaan vektor = ada For cohort keberadaan vektor = N of Valid Cases Value Lower Upper 4.078 1.189 13.991 1.666.979 2.835.408.191.873 54 95% Confidence Interval
Logistic egression Unweighted Cases a Selected Cases Unselected Cas es Case Processing Summary Included in Analysis Mis sing Cases a. If weight is in effect, see classification table for the total number of cases. N Percent 0.0 0.0 De pendent Varia ble Encoding Original Value ada Internal Value 0 1 Block 0: Beginning Block Classification Table a,b Predicted Observed Step 0 keberadaan vektor ada Overall Percentage a. Constant is included in the model. b. The cut value is.500 keberadaan vektor Percentage ada Correct 37 0 100.0 17 0.0 68.5 Va riables in the Equa tion Step 0 Constant B S.E. W ald df Sig. Ex p(b) -.778.293 7.045 1.008.459
Va riables not in the Equa tion Step 0 Variables Overall Statistics deck Sc ore df Sig. 1.102 1.294 1.102 1.294 Block 1: Method = Enter Omnibus Tests of Model Coefficients Step 1 Step Block Model Chi-square df Sig. 1.248 1.264 1.248 1.264 1.248 1.264 Model Summary Step 1-2 Log likelihood 66.025 a Cox & Snell Square.023 Nagelkerke Square.032 a. Estimation terminated at iteration number 5 because parameter estimates changed by less than.001. Classification Table a Predicted Observed Step 1 keberadaan vektor Overall Percentage a. The cut value is.500 ada keberadaan vektor Percentage ada Correct 37 0 100.0 17 0.0 68.5 Variables in the Equation 95.0% C.I.for EXP(B) B S.E. Wald df Sig. Exp(B) Lower Upper Step deck 1.130 1.123 1.013 1.314 3.097.343 27.985 1 a Constant -2.922 2.182 1.793 1.181.054 a. Variable(s) entered on step 1: deck.
Logistic egression Unweighted Cases a Selected Cases Unselected Cas es Case Processing Summary Included in Analysis Mis sing Cases a. If weight is in effect, see classification table for the total number of cases. N Percent 0.0 0.0 De pendent Varia ble Encoding Original Value ada Internal Value 0 1 Block 0: Beginning Block Classification Table a,b Predicted Observed Step 0 keberadaan vektor ada Overall Percentage a. Constant is included in the model. b. The cut value is.500 keberadaan vektor Percentage ada Correct 37 0 100.0 17 0.0 68.5 Va riables in the Equa tion Step 0 Constant B S.E. W ald df Sig. Ex p(b) -.778.293 7.045 1.008.459
Va riables not in the Equa tion Step 0 Variables Overall Statistics ktotk Sc ore df Sig. 6.466 1.011 6.466 1.011 Block 1: Method = Enter Omnibus Tests of Model Coefficients Step 1 Step Block Model Chi-square df Sig. 6.229 1.013 6.229 1.013 6.229 1.013 Model Summary Step 1-2 Log likelihood 61.044 a Cox & Snell Square.109 Nagelkerke Square.153 a. Estimation terminated at iteration number 4 because parameter estimates changed by less than.001. Classification Table a Predicted Observed Step 1 keberadaan vektor Overall Percentage a. The cut value is.500 ada keberadaan vektor Percentage ada Correct 30 7 81.1 8 9 52.9 72.2 Variables in the Equation 95.0% C.I.for EXP(B) B S.E. Wald df Sig. Exp(B) Lower Upper Step ktotk 1.573.642 6.002 1.014 4.821 1.370 16.972 1 a Constant -2.895.942 9.444 1.002.055 a. Variable(s) entered on step 1: ktotk.
Logistic egression Unweighted Cases a Selected Cases Unselected Cas es Case Processing Summary Included in Analysis Mis sing Cases a. If weight is in effect, see classification table for the total number of cases. N Percent 0.0 0.0 De pendent Varia ble Encoding Original Value ada Internal Value 0 1 Block 0: Beginning Block Classification Table a,b Predicted Observed Step 0 keberadaan vektor ada Overall Percentage a. Constant is included in the model. b. The cut value is.500 keberadaan vektor Percentage ada Correct 37 0 100.0 17 0.0 68.5 Va riables in the Equa tion Step 0 Constant B S.E. W ald df Sig. Ex p(b) -.778.293 7.045 1.008.459
Va riables not in the Equa tion Step 0 Variables Overall Statistics kmtot Sc ore df Sig. 13.636 1.000 13.636 1.000 Block 1: Method = Enter Omnibus Tests of Model Coefficients Step 1 Step Block Model Chi-square df Sig. 13.557 1.000 13.557 1.000 13.557 1.000 Model Summary Step 1-2 Log likelihood 53.716 a Cox & Snell Square.222 Nagelkerke Square.312 a. Estimation terminated at iteration number 5 because parameter estimates changed by less than.001. Classification Table a Predicted Observed Step 1 keberadaan vektor Overall Percentage a. The cut value is.500 ada keberadaan vektor Percentage ada Correct 30 7 81.1 5 12 70.6 77.8 Variables in the Equation 95.0% C.I.for EXP(B) B S.E. Wald df Sig. Exp(B) Lower Upper Step kmtot 2.331.678 11.822 1.001 10.286 2.724 38.837 1 a Constant -4.123 1.077 14.657 1.000.016 a. Variable(s) entered on step 1: kmtot.
Logistic egression Unweighted Cases a Selected Cases Unselected Cas es Case Processing Summary Included in Analysis Mis sing Cases a. If weight is in effect, see classification table for the total number of cases. N Percent 0.0 0.0 De pendent Varia ble Encoding Original Value ada Internal Value 0 1 Block 0: Beginning Block Classification Table a,b Predicted Observed Step 0 keberadaan vektor ada Overall Percentage a. Constant is included in the model. b. The cut value is.500 keberadaan vektor Percentage ada Correct 37 0 100.0 17 0.0 68.5 Va riables in the Equa tion Step 0 Constant B S.E. W ald df Sig. Ex p(b) -.778.293 7.045 1.008.459
Va riables not in the Equa tion Step 0 Variables Overall Statistics datotk Sc ore df Sig. 13.120 1.000 13.120 1.000 Block 1: Method = Enter Omnibus Tests of Model Coefficients Step 1 Step Block Model Chi-square df Sig. 13.393 1.000 13.393 1.000 13.393 1.000 Model Summary Step 1-2 Log likelihood 53.880 a Cox & Snell Square.220 Nagelkerke Square.308 a. Estimation terminated at iteration number 5 because parameter estimates changed by less than.001. Classification Table a Predicted Observed Step 1 keberadaan vektor Overall Percentage a. The cut value is.500 ada keberadaan vektor Percentage ada Correct 28 9 75.7 4 13 76.5 75.9 Variables in the Equation 95.0% C.I.for EXP(B) B S.E. Wald df Sig. Exp(B) Lower Upper Step datotk 2.314.688 11.299 1.001 10.111 2.624 38.965 1 a Constant -4.260 1.154 13.633 1.000.014 a. Variable(s) entered on step 1: datotk.
Logistic egression Unweighted Cases a Selected Cases Unselected Cas es Case Processing Summary Included in Analysis Mis sing Cases a. If weight is in effect, see classification table for the total number of cases. N Percent 0.0 0.0 De pendent Varia ble Encoding Original Value ada Internal Value 0 1 Block 0: Beginning Block Classification Table a,b Predicted Observed Step 0 keberadaan vektor ada Overall Percentage a. Constant is included in the model. b. The cut value is.500 keberadaan vektor Percentage ada Correct 37 0 100.0 17 0.0 68.5 Va riables in the Equa tion Step 0 Constant B S.E. W ald df Sig. Ex p(b) -.778.293 7.045 1.008.459
Va riables not in the Equa tion Step 0 Variables Overall Statistics gtotk Sc ore df Sig. 5.297 1.021 5.297 1.021 Block 1: Method = Enter Omnibus Tests of Model Coefficients Step 1 Step Block Model Chi-square df Sig. 5.131 1.023 5.131 1.023 5.131 1.023 Model Summary Step 1-2 Log likelihood 62.142 a Cox & Snell Square.091 Nagelkerke Square.127 a. Estimation terminated at iteration number 4 because parameter estimates changed by less than.001. Classification Table a Predicted Observed Step 1 keberadaan vektor Overall Percentage a. The cut value is.500 ada keberadaan vektor Percentage ada Correct 29 8 78.4 8 9 52.9 70.4 Variables in the Equation 95.0% C.I.for EXP(B) B S.E. Wald df Sig. Exp(B) Lower Upper Step gtotk 1.406.629 4.995 1.025 4.078 1.189 13.991 1 a Constant -2.693.935 8.300 1.004.068 a. Variable(s) entered on step 1: gtotk.
Logistic egression Unweighted Cases a Selected Cases Unselected Cas es Case Processing Summary Included in Analysis Mis sing Cases a. If weight is in effect, see classification table for the total number of cases. N Percent 0.0 0.0 De pendent Varia ble Encoding Original Value ada Internal Value 0 1 Block 0: Beginning Block Classification Table a,b Predicted Observed Step 0 keberadaan vektor ada Overall Percentage a. Constant is included in the model. b. The cut value is.500 keberadaan vektor Percentage ada Correct 37 0 100.0 17 0.0 68.5 Va riables in the Equa tion Step 0 Constant B S.E. W ald df Sig. Ex p(b) -.778.293 7.045 1.008.459
Va riables not in the Equa tion Step 0 Variables Overall Statistics ktotk kmtot datotk gtotk Sc ore df Sig. 6.466 1.011 13.636 1.000 13.120 1.000 5.297 1.021 21.556 4.000 Block 1: Method = Enter Omnibus Tests of Model Coefficients Step 1 Step Block Model Chi-square df Sig. 24.286 4.000 24.286 4.000 24.286 4.000 Model Summary Step 1-2 Log likelihood 42.987 a Cox & Snell Square.362 Nagelkerke Square.509 a. Estimation terminated at iteration number 6 because parameter estimates changed by less than.001. Classification Table a Predicted Observed Step 1 keberadaan vektor Overall Percentage a. The cut value is.500 ada keberadaan vektor Percentage ada Correct 36 1 97.3 7 10 58.8 85.2 Variables in the Equation 95.0% C.I.for EXP(B) B S.E. Wald df Sig. Exp(B) Lower Upper Step ktotk 1.229.795 2.392 1.122 3.418.720 16.228 1 a kmtot 1.538.801 3.683 1.055 4.655.968 22.387 datotk 1.677.847 3.923 1.048 5.348 1.018 28.108 gtotk 1.466.833 3.097 1.078 4.330.846 22.153 Constant -9.206 2.501 13.544 1.000.000 a. Variable(s) entered on step 1: ktotk, kmtot, datotk, gtotk.
Logistic egression Unweighted Cases a Selected Cases Unselected Cas es Case Processing Summary Included in Analysis Mis sing Cases a. If weight is in effect, see classification table for the total number of cases. N Percent 0.0 0.0 De pendent Varia ble Encoding Original Value ada Internal Value 0 1 Block 0: Beginning Block Classification Table a,b Predicted Observed Step 0 keberadaan vektor ada Overall Percentage a. Constant is included in the model. b. The cut value is.500 keberadaan vektor Percentage ada Correct 37 0 100.0 17 0.0 68.5 Va riables in the Equa tion Step 0 Constant B S.E. W ald df Sig. Ex p(b) -.778.293 7.045 1.008.459
Variables not in the Equation Step 0 Variables Overall Statistics kmtot datotk gtotk Score df Sig. 13.636 1.000 13.120 1.000 5.297 1.021 20.192 3.000 Block 1: Method = Enter Omnibus Tests of Model Coefficients Step 1 Step Block Model Chi-square df Sig. 21.827 3.000 21.827 3.000 21.827 3.000 Step 1 a. Model Summary -2 Log Cox & Snell Nagelkerke likelihood Square Square 45.446 a.332.467 Estimation terminated at iteration number 5 because parameter estimates changed by less than.001. Classification Table a Predicted Observed Step 1 keberadaan vektor Overall Percentage a. The cut value is.500 ada keberadaan vektor Percentage ada Correct 33 4 89.2 6 11 64.7 81.5 Step 1 a kmtot datotk gtotk Constant Va riables in the Equa tion B S.E. W ald df Sig. Ex p(b) Lower Upper 1.434.783 3.351 1.067 4.194.904 19.463 1.905.819 5.414 1.020 6.721 1.350 33.453 1.390.809 2.948 1.086 4.014.821 19.612-7.574 1.993 14.437 1.000.001 a. Variable(s) entered on step 1: kmtot, datotk, gtotk. 95.0% C.I.for EXP(B)
Logistic egression Unweighted Cases a Selected Cases Unselected Cas es Case Processing Summary Included in Analysis Mis sing Cases a. If weight is in effect, see classification table for the total number of cases. N Percent 0.0 0.0 De pendent Varia ble Encoding Original Value ada Internal Value 0 1 Block 0: Beginning Block Classification Table a,b Predicted Observed Step 0 keberadaan vektor ada Overall Percentage a. Constant is included in the model. b. The cut value is.500 keberadaan vektor Percentage ada Correct 37 0 100.0 17 0.0 68.5 Va riables in the Equa tion Step 0 Constant B S.E. W ald df Sig. Ex p(b) -.778.293 7.045 1.008.459
Variables not in the Equation Step 0 Variables Overall Statistics kmtot datotk Score df Sig. 13.636 1.000 13.120 1.000 17.912 2.000 Block 1: Method = Enter Omnibus Tests of Model Coefficients Step 1 Step Block Model Chi-square df Sig. 18.735 2.000 18.735 2.000 18.735 2.000 Model Summary Step 1-2 Log likelihood 48.538 a Cox & Snell Square.293 Nagelkerke Square.412 a. Estimation terminated at iteration number 5 because parameter estimates changed by less than.001. Classification Table a Predicted Observed Step 1 keberadaan vektor Overall Percentage a. The cut value is.500 ada keberadaan vektor Percentage ada Correct 33 4 89.2 7 10 58.8 79.6 Variables in the Equation 95.0% C.I.for EXP(B) B S.E. Wald df Sig. Exp(B) Lower Upper Step kmtot 1.703.743 5.251 1.022 5.492 1.279 23.573 1 a datotk 1.694.754 5.052 1.025 5.441 1.242 23.831 Constant -5.768 1.455 15.713 1.000.003 a. Variable(s) entered on step 1: kmtot, datotk.