<![CDATA[The main problems in determining warehouse location include high operational costs, inadequate accessibility and infrastructure, and strict and complex local regulations. In addition, environmental risks and natural disasters, as well as economic fluctuations and market dynamics also add to the challenge of choosing an optimal location. The purpose of this study is to apply the Entropy and ARAS methods in evaluating the potential of optimal warehouse locations, thereby providing clear and structured guidance for decision-makers in choosing the optimal warehouse location to meet the company's operational and strategic needs. The implementation of the entropy and ARAS methods in determining the best warehouse location involves a systematic approach in evaluating several criteria that are important for optimal decision-making. The Entropy method helps in objectively assessing the importance of each criterion by quantifying the uncertainty or variation present in the data. The ARAS method complements this by allowing comparative analysis of alternative warehouse locations based on their performance against ideal criteria, taking into account both quantitative and qualitative aspects. Thus, both methods provide a solid framework for selecting warehouse locations that not only meet logistics requirements efficiently but are also in line with strategic business objectives, ensuring a well-informed decision-making process in supply chain management and logistics. The results of the ranking of the best warehouse location selection using the entropy and ARAS methods show AB Location as the first rank with a value of 0.9781, DD Location as the second place with a value of 0.8362, and IP Location as the third place with a value of 0.8143.]]>
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