MODELING FACTORS THAT INFLUENCE POVERTY LEVEL IN SUMATERA USING SPATIAL REGRESSION MODELS

Abstract

Poverty is a condition of a person's inability to fulfill basic needs such as food, clothing, shelter, school and health. Poverty is still a major unresolved problem in Indonesia, including the island of Sumatra. Based on BPS data in 2022, the number of poor people in Sumatera is the second after Java. This research was conducted with the aim of analyzing the factors that explain the level of poverty in Sumatera. The method that will be used is spatial regression modeling, including the General Nested Spatial Model (GNSM), Spatial Autoregressive Model (SAR), Spatial Error Model (SEM) and Spatial Autoregressive and Moving Average Model (SARMA). The dependent variable is Poverty Level (Miskin) and the independent variables include Population Density (KP), Average Years of Schooling (RLS), Human Development Index (IPM), Open Unemployment Rate (TPT) and Regency Minimum Wage (UMK). Based on the result of this study, the Spatial Autoregressive and Moving Average Model is the best model, with the smallest AIC value, namely 305.32. The only factor that has a significant influence on the poverty level is the Human Development Index (IPM).