Analysis of factors causing the number of poor people in DKI Jakarta using spatial autoregressive Poisson model

Poverty is one of the problems that happened in DKI Jakarta. The case of poverty in DKI Jakarta can be viewed from a geographical perspective, namely because the regions in DKI Jakarta are interconnected. This study aims to determine the factors that influence spatially and non-spatially on the number of poor people in DKI Jakarta used the Poisson Regression and Spatial Autoregressive Poisson Model. Data used in this research came from Badan Pusat Statistika 2019 [1]. The parameter estimation method in this study uses the maximum likelihood method. The results showed that spatial (ρ) and non-spatial factors (β) had a significant effect with alpha 5%. Based on the null deviance, Poisson Regression Model gave a smaller value than the Spatial Autoregressive Poisson Model.