Comparison Poisson Regression And Spatial Autoregressive (SAR) Poisson (Case Study : In Preventing The Malnutrition Factors In Java Island)

Abstract

Indonesia is one of the developing countries whose population is always increasing every year as well as causing the population density in Indonesia to increase also. Based on the results of the population census in 2000 and 2010, Java island is the island with the highest population density. It can be caused by the number of high malnutrition events as well. Malnutrition is a major factor in infant under-five mortality. Based on world health statistics, malnutrition is the cause of one-third of child mortality under 5 years. This study aims to determine risk factors in under five children in Java island. The percentage of malnutrition sufferer from Java Island is 4,34%. Therefore it can be said that the incidence suffering from malnutrition in children under five in Java is a rare event, so it follows the distribution of Poisson. Where the Poisson distribution can be said as a very rare occurrence occurs. The result of the Moran’s I tests states that there are spatial dependencies on severe malnutrition’s rate of children under five years in Java Island. Therefore, Spatial Autoregressive (SAR) Poisson method is used in this experiment. The aims of this study is to compare factors that influence the malnutrition of children under five in Java Island using Poisson Regression and Spatial Autoregressive (SAR) Poisson. The result Variables which significantly affect severe malnutrition on Java Island through Poisson Regression and SAR Poisson method are the number of household with clean healthy living behavior (X_2, the number of houses with good health status (X_3), the number of household with access to source of clean water (X_4), maternal and child health center with active status (X_5), Vitamin A supplementation coverage[X]_7) and the number of babies given breastfeeding exclusively [X]_8)The differences are variable the number of babies with low birth weight [X] 1) is not significantly affecting severe malnutrition through SAR Poisson method.