Analisis Kemiskinan di Provinsi Jawa Tengah Menggunakan Metode Regresi Spasial

Abstract

Poverty is a trouble in economics, so it must be cured or at least reduced. Problem of poverty is an issue that is complex and multidimensional. The problem of poverty in province of Central Java is still high when compared to other provinces in Java. The number of poor people in Central Java is the second largest after East Java.The purpose of research was to determine the variables that significantly affect poverty in each district, and determining a model for estimating the incidence of poverty in each district. The analytical method used in this research is multiple linear regression and spatial regression. The results showed that the significant variables or affect poverty on multiple linear regression model only the population works in the agricultural sector variable(X2), while SAR models and SEM models, the significant variables of poverty are the rate of open unemployment variable (X1), the population works in the agricultural sector (X2). The role model for case of poverty in province of Central Java is SEM model. This is evidenced by AIC SEM 225,179 smaller than the SAR model 228,555 and the value of R2 SEM 73,01% is greater than SAR model 70,90%.