Pemodelan Tingkat Kemiskinan di Provinsi Aceh Menggunakan Distribusi Poisson dan Binomial Negatif - Tampubolon, Elza Ully Tiara; Kusuma, Bagus (Lembaga Pendidikan dan Penelitian Manggala Institute, 2025)
This study aims to model the poverty rate in Aceh Province using the Generalized Linear Models (GLMs) approach with the Integrated Nested Laplace Approximation (INLA) method. The models used in this study include Poisson and Negative Binomial regression. The data used includes variables of per capita expenditure, population density, average years of schooling, open unemployment rate, and labor force participation. Multicollinearity tests were conducted using Tolerance and Variance Inflation Factor (VIF) values to ensure the absence of multicollinearity problems between predictor variables. The results show that the Negative Binomial model is better than the Poisson model, as indicated by the smaller WAIC value. The average years of schooling variable has a significant negative effect, while the open unemployment rate has a significant positive effect on the poverty rate. Meanwhile, the variables of expenditure per capita, population density, and labor force participation make smaller and partially insignificant contributions in the model. Thus, increasing access to education and reducing unemployment are key factors in poverty alleviation efforts in Aceh Province. The results of this study are expected to serve as a reference for policy makers in formulating effective strategies to reduce poverty.