Developing a Poverty Model in Papua using Geographically Weighted Regression

Abstract

Poverty is one of the world's main problems, which has been very difficult to overcome. The poverty rate has influences on economic growth in an area. The greater the poverty rate in an area, the more difficult it is for an area to grow economically. Many factors affect the level of poverty. Geographical location, level of education, population growth in each region, significantly affect the poverty level. The many factors that affect the poverty level make it difficult for us to predict which factors will influence the level of poverty in an area, making it difficult for us to solve the problem. This research was made to predict what factors influence the level of poverty in Papua, Indonesia. This study uses a Geographically Weighted Regression (GWR) method due to the existence of spatial heterogeneity. It produces model estimates that are local for each location and different from other locations to get a model with the most influential factors in each region. The results of this study are as follows. First, agricultural employees affected the poverty rate in each location in Papua. Second, house area and households with access to safe water are significant variables in Yapen, Biak Numfor, and Supiori.