Implementation of Multi-Criteria in Supply Chain Optimization Analysis of the Livestock Sector on Java Island

Abstract

The rapid development of technology has had a significant impact on various sectors, including the livestock industry. This study examines the application of the Multi-Criteria Decision Making (MCDM) method, especially the Analytical Hierarchy Process (AHP), to optimize the supply chain in the livestock sector in Java. The purpose of this study is to determine the most efficient livestock production area by evaluating criteria such as production quantity, average production, production cost, and percentage increase in production over a certain period. In addition, this research integrates Artificial Intelligence (AI) as a controller to improve data management and monitor the livestock production process. This study uses quantitative methods to analyze supply chain data from Central Java, West Java, and East Java. The findings show that Central Java has the highest livestock production efficiency with an index of 0.4511, contributing significantly to the island's overall production. The study concluded that integrating AI into supply chain management can significantly improve efficiency and productivity in the livestock sector.