Analisis Korelasi Variabel dan Pemodelan Regresi Non-linear Ketenagakerjaan Terhadap PDRB Provinsi Indonesia Tahun 2021 dengan GLM dan INLA

Abstract

Economic growth is a key indicator in assessing the welfare of a region, with Gross Regional Domestic Product (GRDP) serving as one of its primary measures. This study aims to analyze the influence of various factors on GRDP in 35 provinces of Indonesia using Generalized Linear Models (GLM) and Integrated Nested Laplace Approximation (INLA) approaches. The analyzed variables include Open Unemployment Rate (OUR), Crime Rate (CR), Poverty Rate (PR), Population (POP), and Human Development Index (HDI). The data were obtained from Indonesia's Central Bureau of Statistics (BPS) for 2021. GLM was selected to capture nonlinear relationships with Gamma distribution and log link function, while INLA was utilized to estimate model parameters using a Bayesian approach, accounting for spatial data structures. This study provides a foundation for policymakers to design more effective and data-driven economic development strategies.