Anik Djuraidah, Dani Al Mahkya, Ayu Sofia, Fatkhurokhman Fauzi
Food security is a crucial indicator of a country’s development, influenced by various social, economic, and health factors. This study aims to analyze the factors affecting the food security index (FSI) in Indonesia by considering spatial variations using eigenvector spatial filtering (ESF) approach. This method provides more stable parameter estimates compared to global regression and geographically weighted regression (GWR), which often suffer from multicollinearity and autocorrelation issues. The study utilizes data from 514 districts/cities in Indonesia with eight explanatory variables, including life expectancy, poverty rate, and population growth. The results indicate that the random effect spatial filtering varying coefficient (RE ESF-VC) model achieves a higher goodness-of-fit compared to the GWR, and random effect eigenvector spatial filtering (RE ESF) models, with an adjusted R² of 0.801. The model identifies that the key factors influencing FSI vary spatially, with the Percentage of Poor Population being the most locally significant factor. These findings provide valuable insights for local governments in designing more effective and region-specific food security policies. © 2026 The Korean Statistical Society, and Korean International Statistical Society. All rights reserved.
School of Data Science, Mathematics, and Informatics, IPB University, Bogor, Indonesia; Institut Teknologi Sumatera, Indonesia; Department of Statistics, Universitas Muhammadiyah Semarang, Indonesia
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