Decision Support System in Determining the Optimal Raw Material Supplier Using a Combination of Entropy and MOORA

Abstract

The selection of the right raw material supplier plays a crucial role in ensuring the efficiency and sustainability of supply chain management. However, the decision-making process is often complex due to the multiple criteria that must be considered simultaneously, such as quality, price, delivery timeliness, production capacity, and flexibility. To address this challenge, this study applies a decision support system that integrates the Entropy method for objective weighting of criteria and the MOORA method for ranking alternatives. Entropy weighting provides an unbiased determination of the importance of each criterion based on data variation, while MOORA delivers a systematic ranking of suppliers by combining benefit and cost criteria into a comprehensive performance score. The results of the analysis on eight supplier alternatives show that Supplier S8 achieves the highest ranking, followed by Supplier S3 and Supplier S6, indicating their superior ability to meet the defined criteria, especially in capacity and flexibility. Meanwhile, Supplier S4 ranks the lowest, reflecting its relatively weaker performance across several aspects. These findings demonstrate that the combination of Entropy and MOORA provides a reliable, objective, and transparent framework to support decision-making in supplier selection.