FORUM STATISTIKA DAN KOMPUTASI
Vol. 15 No. 1 (2010)

PEMODELAN RESIKO PENYAKIT KAKI GAJAH (FILARIASIS) DI PROVINSI PAPUA DENGAN REGRESI ZERO-INFLATED POISSON

Sri Pingit Wulandari (Unknown)
Brodjol Sutijo (Unknown)
Ika Rahmawati (Unknown)



Article Info

Publish Date
01 Apr 2010

Abstract

The goverment has established elimination of filariasis tropical disease as one of the priority programs. One of the districts that has become a target is Papua. The total amount of  filariasis victim on every regency/city in Papua district can be assumed to follow a Poisson distribution. So Poisson regression method is a suitable method to know the influence factor of filariasis disease. Poisson regression model assumes equidispersion, that is equality of mean and variance of the response variable. Overdispersion test shows that the variance of the response variable exceeds its mean value. So the model is modified into zeroinflated Poisson (ZIP) regression model (logit and log). ZIP logit regression model shows that the quantity of filariasis victim in every regency/city in Papua district with zero count is influenced by the percentage of household members who sleep inside mosquito net, the percentage of household members who sleep inside insecticide musquito net, and the percentage of house-holds who keep pet (dog/cat/rabbit). While ZIP regression on log model shows that the increasing number of percentage household who keeps their pet will enhance the quantity of filariasis victim  in Papua district as many as two people. Regencies/cities which need to get special attention through an elimination program of filariasis are Asmat, Tolikara, Supiori, Yapen Waropen, and Jayapura city.

Copyrights © 2010






Journal Info

Abbrev

statistika

Publisher

Subject

Mathematics

Description

Forum Statistika dan Komputasi (ISSN:0853-8115) was published scientific papers in the area of statistical science and the applications. It is issued twice in a year. The papers should be research papers with, but not limited to, following topics: experimental design and analysis, survey methods and ...