Modeling Human Development Index Based on Socio-Economic Factors in West Sumatra Using Local Polynomial Regression

Abstract

Human development is a central concern in regional policy because economic advancement does not necessarily translate into improved quality of life. However, research modelling nonlinear relationships between the Human Development Index (HDI) and socioeconomic factors across the regencies and municipalities of West Sumatra using Local Polynomial Regression (LPR) remains limited. This study aims to model HDI based on the senior high school net enrolment rate (NER), gross regional domestic product (GRDP), and population density. A quantitative, nonexperimental, cross-sectional design was employed using 2023 secondary data from Statistics Indonesia covering 19 regencies and municipalities. The data were analysed using nonparametric LPR with a local-linear estimator and optimal bandwidth selection. The findings indicate that all three predictors are positively associated with HDI, with senior high school NER exhibiting the strongest correlation. The model achieved an R² of 0.9147, a root mean squared error of 1.3458, and a mean absolute error of 1.0292, demonstrating its ability to capture nonlinear patterns and explain regional variation in HDI. This study contributes to regional development modelling by demonstrating the applicability of LPR to multidimensional human development data. The findings provide an empirical basis for more context-sensitive development policies that integrate educational participation, economic capacity, and population distribution.