Spatial Regression Analysis in Determining the Influencing Factors on Poverty in West Java

Abstract

Poverty is still a very important issue in Indonesia, hence needs government's concern to overcome it. Handling this problem can be considered as modelling the poverty based on the factors that cause it. According to the law of geography proposed by Tobler, to overcome poverty in a region, the government must also consider the situation of its neighbours. Tobler's law is used as a pillar of study in spatial data analysis. If an observation in a location has spatial elements, then the data analysis using a simple regression model, will not as accurate as that which pays attention to spatial element. Therefore, we use a regression analysis that takes into account the existence of spatial influences, called spatial regression analysis. The models formed in spatial regression analysis are spatial lag model or spatial autoregressive model (SAR), spatial error model (SEM), and general spatial model. In this research we use spatial autoregressive model (SAR).