Implementation of Panel Data Regression in the Analysis of Factors Affecting Poverty Levels in Bengkulu Province in 2017-2020: Implementation of Panel Data Regression - Aprilia Dewi Anggraeni Chairunnisa; Achmad Fauzan (Fakultas Matematika dan Ilmu Pengetahuan Alam, 2023)
Economic resilience is certainly an important target in every country or region. One of the main concerns in the economy of a country is poverty. This study aims to explore data with panel data regression that was formed and find factors that affect poverty in Bengkulu province from 2017 to 2020. The secondary data utilized were obtained from the Central Bureau of Statistics (BPS) of the province of Bengkulu. The independent variables used are Gross Regional Domestic Product (GRDP), Human Development Index (HDI), Life Expectancy (LE), and Average Years of Schooling (AYS), while the dependent variable is the percentage of poverty in the form of per region. The best panel data model obtained is the Fixed Effect Model (FEM) model with a cross-section. Based on the results obtained, the significant variable in this model is the GRDP variable. From the prediction results, the values ​​obtained from Mean Absolute Percentage Error (MAPE), Mean Square Error (MSE), and Root Mean Square Error (RMSE) respectively are 6.59% for MAPE, 5.48 for MSE, and 2.4 for RMSE indicating that panel data analysis is very very good in terms of predicting poverty in Bengkulu province