UNIVERSITAS AIRLANGGA



Detail Article

Jurnal Biometrika dan Kependudukan

ISSN 2302707X

Vol. 4 / No. 1 / Published : 2015-07

Order : 3, and page :14 - 24

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Original Article :

Prediksi jumlah kasus baru kusta dengan metode

Author :

  1. Fitri Rachmillah Fadmi*1
  1. Mahasiswa Fakultas Kesehatan Masyarakat

Abstract :

Poisson regression was obtained from the Poisson distribution, which is a theoretical distribution associated with a discrete random variable count, where each event follows the Poisson distribution. Leprosy data in Buton isone example of the data count. The main problem of the Poisson regression is when applied to the spatial data,the heterogeneity will occur. Spatial heterogeneity arises because of the condition of data in each location is notthe same, both in terms of geographical, socio-cultural and other things that lie behind them. One impact of theemergence of spatial heterogeneity is regression parameters are varying spatially, so as to solve the problemson data spatial, the spatial modellingis done. Spatial modeling is appropriate for use Geographically WeightedPoisson Regression (GPWR). This study aims to determine the best models on the number of new cases of leprosyin Buton District in 2013. Studies conducted a study of non-reactive or unobtrusive method. The experiment wasconducted in Buton in Southeast Sulawesi province May-June 2014. Units of analysis in this study is the data newcases of leprosy in every district in Buton. The results showed Geographicaly Weighted Poisson Regression Model(GWPR) yields the smallest AIC value, so the best modeling for the number of new cases of leprosy in Buton isGeographicaly Weighted Poisson Regression Model (GWPR) than the model Poisson regression model.

Keyword :

poisson regression, geographicaly weighted, leprosy ,


References :

Fotheringham C., Brundson., A.S. Charlton. M.,(2002) Geographically Weighted Regression: the analysis of spatially varying relationship. England : John Wiley and Sons Ltd

Djauzi, R,(2009) Raih Kembali Kesehatan. Jakarta. : Penerbit Buku Kompas.

Departemen Kesehatan Republik Indonesia.,(2004) Indikator Indonesia Sehat 2010. Jakarta : Depkes RI

Budiarto, E., Dewi, A,(2003) Pengantar Epidemiologi Edisi 2 Jakarta. : Penerbit Buku Kedokteran EGC

Ardiyanti, S., T., Purhadi.,(2009) Pemodelan Angka Kematian Bayi dengan Pendekatan Geographically Weighted Poisson Regression (GWPR) di Provinsi Jawa Timur. ITS. Surabaya. Skripsi. Surabaya : FMIPA-ITS





Archive Article

Cover Media Content

Volume : 4 / No. : 1 / Pub. : 2015-07
  1. Hubungan Peran Keluarga Dan Komunitas Pecandu Terhadap Motivasi Untuk Sembuh Pengguna Narkoba Jarum Suntik
  2. Faktor Yang Meningkatkan Risiko Premenstrual Syndrome Pada Mahasiswi
  3. Prediksi Jumlah Kasus Baru Kusta Dengan Metode
  4. Pengaruh Usia, Paritas Dan Anemia Terhadap Kejadian Perdarahan Post Partum
  5. Faktor Risiko Kejadian Asfiksia Neonatorum Di Rsud Kanjuruhan Malang
  6. Hubungan Faktor Sosioekonomi Orang Tua Dengan Perilaku Seksual Pranikah Remaja
  7. Kekerasan Terhadap Istri Pada Wanita Menikah Usia Muda Dan Usia Ideal
  8. Faktor Yang Memengaruhi Preferensi Jumlah Anak
  9. Pengaruh Faktor Spasial Kelahiran Terhadap Kepadatan Penduduk Di Jawa Timur Tahun 2012
  10. Faktor Yang Memengaruhi Unmet Need Keluarga Berencana
  11. Pengaruh Paritas Dan Penggunaan Pil Kontrasepsi Kombinasi Terhadap Kejadian Kanker Payudara
  12. Analisis Spasial Untuk Mengidentifikasi Determinan Angka Kematian Ibu Di Provinsi Jawa Timur Tahun 2012

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