Utilizing Multi-Arm Bandit and Partitioning Around Medoids for Clustering Food Security Conditions in Sumatra Island

Abstract

This study applies the Multi Arm-Bandit (MAB) and Partition Around Medoid (PAM) methods to cluster food security status in Sumatra Island in 2022. Food issues in Indonesia are becoming increasingly complex with challenges covering food availability, accessibility and food security. Data were obtained from the Food Security and Vulnerability Atlas (FSVA). The MAB method was used to identify the most influential variables in decision-making, while the PAM method was used for clustering based on medoids. The results showed that the PAM method was effective in categorizing provinces of Sumatra Island based on food security variables. Additionally, significant variables identified included poverty, food expenditure, disease rate, and stunting. This study provides important contributions to the government and the National Food Agency in designing food security improvement programs in various regions of Sumatra Island and serves as a reference for other researchers applying similar methods in complex data analysis.