Spatial Autoregressive Poisson Model for Detecting Influential Factors on the Number of patients with Malnutrition in the Province of East Java

Abstract

One indicator of poverty can be seen from the large of people with malnutrition. Genesis residents suffer from malnutrition in the Province of East Java is a rare occurrence, so the incidence of people suffering from malnutrition can be assumed to follow a Poisson distribution. Although the incidence of people suffering from malnutrition including a rare occurrence, but malnutrition is a serious problem that requires special handling because it has led to the decline in resource quality. For that use spatial autoregressive Poisson models to detect factors that influence the number of people with malnutrition. Based on the results of this study was obtained that the factors that influence the number of people with malnutrition are spatial and non-spatial. Spatial factor that predispose to a particular location is the location of the neighbors. This means that the number of people with malnutrition in a region or a nearby location will affect the number of malnourished people in the surrounding locations. While non-spatial factors that influence the number of people with malnutrition are the number of families residing in the slums, the area of land use structure is not enough irrigation, the number of health workers living in rural or village, and the number of per capita gross regional domestic product. The coefficient of determination for the SAR Poisson model was 0.57. Based on the scan statistic method obtained four clusters of hotspot areas.

Gizi buruk adalah keadaan kurang zat gizi tingkat berat yang disebabkan oleh rendahnya konsumsi energi dan protein dalam waktu cukup lama yang ditandai dengan tidak sesuainya berat badan dengan umur (BPS 2008). Gizi buruk secara langsung disebabkan oleh kurangnya asupan makanan dan penyakit infeksi, sedangkan secara tidak langsung disebabkan oleh ketersediaan pangan, sanitasi, pelayanan kesehatan, pola asuh, kemampuan daya beli keluarga, pendidikan, dan pengetahuan. Masalah gizi buruk membutuhkan penanganan yang tepat, karena konsekuensinya dapat menimbulkan penurunan kualitas sumber daya manusia. . Jawa Timur merupakan salah satu provinsi yang memiliki jumlah penderita gizi buruk terbanyak di Indonesia. Dalam upaya menangani banyaknya jumlah penderita gizi buruk diperlukan upaya untuk mengetahui faktor-faktor yang mempengaruhinya baik spasial maupun nonspasial. Jumlah warga yang menderita gizi buruk merupakan data cacahan (count data) dan kejadian warga menderita gizi buruk merupakan kejadian yang jarang terjadi, sehingga dalam penelitian ini menggunakan model Spatial Autoregressive Poisson (SAR Poisson).