Analysis of Food Security Index in East Kalimantan Using Panel Regression and K-Means Clustering - Diana Nurlaily; Nabila Putri Bareng; Milka Yosep; Revalina Putria Hidayat (STMIK Widya Cipta Dharma, 2026)
This study aims to identify indicators that significantly influence the Food Security Index (IKP) of districts/cities in East Kalimantan Province and to group regions based on their food security characteristics. Food security is a crucial issue because it relates to the availability, accessibility, and utilization of food, which are influenced by socioeconomic conditions, education, health, and basic infrastructure. Differences in characteristics between regions in East Kalimantan encourage the need for analysis that can explain the influence of variables both spatially and temporally. The methods used in this study are panel data regression and K-Means Clustering. Panel data regression is applied to analyze variables that significantly influence the IKP, while the selection of the best model is carried out through the Chow Test, Hausman Test, and Lagrange Multiplier Test. Furthermore, the K-Means Clustering method is used to group districts/cities based on food security indicators. The results show that the best model is the Common Effect Model (CEM) with a coefficient of determination of 91.7%. Variables proven to significantly influence the IKP include rice production, poverty rate, per capita expenditure, electricity access, average length of schooling, life expectancy, and access to safe drinking water. Furthermore, the results of the K-Means Clustering analysis yielded three regional groups with distinct food security characteristics, which can serve as a basis for formulating more targeted food security policies in East Kalimantan.