<![CDATA[Gender empowerment remains a multidimensional development challenge in West Sumatra, where regional disparities reflect interconnected educational, economic, political, health, demographic, and infrastructural factors. This study aims to model the Gender Empowerment Index (GEI) across 19 regencies and municipalities in West Sumatra in 2024, identify its relevant determinants, and determine the dominant predictor using Group LASSO. A quantitative research design was employed using secondary data from Statistics Indonesia, comprising 22 predictors classified into six dimensions. All 19 regions were included through census sampling. The data were standardised, assessed for multicollinearity, and analysed using Group LASSO, with K-fold cross-validation applied to determine the optimal penalty parameter. The optimal λ value of 0.2392388 retained 14 predictors and produced a mean squared error of 1.190105 and an R² of 0.985264. The proportion of women serving in Regional People’s Representative Councils emerged as the dominant predictor, with the largest coefficient of 0.892008. These findings demonstrate the utility of Group LASSO for selecting relevant predictors in a multidimensional regional dataset and provide empirical evidence for establishing gender-empowerment policy priorities. The results particularly underscore the importance of women’s political representation in efforts to strengthen gender empowerment across West Sumatra.]]>
