Enhancing Food Security Analysis in South Sulawesi Using Robust Mixed Geographically and Temporally Weighted Regression with M-Estimator

Abstract

MGTWR (Mixed Geographically and Temporally Weighted Regression) combines a global linear regression model with GTWR by incorporating spatial and temporal dimensions. However, it remains sensitive to outliers, which can reduce accuracy. To address this limitation, a robust regression approach with the M-Estimator was applied to model the food security index in South Sulawesi Province from 2018 to 2022. The resulting Robust MGTWR (RMGTWR) model demonstrated improved performance, with a lower AIC ( ) and a high explanatory power ( ). Key factors influencing food security include the ratio of normative consumption per capita to net production, the percentage of households with a proportion of expenditure on food more significant than 65% of total spending, the percentage of households without access to electricity, the percentage of households without access to clean water, and the percentage of stunting toddlers. These findings highlight the effectiveness of RMGTWR with M-Estimator in addressing data irregularities and provide valuable insights for policymakers in designing targeted strategies to strengthen food security in South Sulawesi Province.