<![CDATA[Supplier selection is a crucial process in supply chain management, where companies must determine the best suppliers who are able to meet their needs based on various criteria. Companies often face challenges in managing the various factors that influence supplier selection decisions, suppliers that offer low prices may not always provide the best quality or consistent delivery times. Optimizing supplier selection through the DSS approach, companies can build stronger relationships with high-performing suppliers, while improving overall business resilience and competitiveness. The combination of the TOPSIS method and entropy weighting in supplier selection optimization provides a robust approach to evaluating and selecting the best suppliers based on predetermined criteria. This combination not only improves objectivity and accuracy in the evaluation process, but also allows decision-makers to consider trade-offs between various criteria more effectively. The purpose of the research of the combination of the TOPSIS method and entropy weighting in optimizing supplier selection is to produce objective and data-based criteria weighting through the application of the entropy weighting method, thereby reducing subjectivity in the supplier selection process. The results of the preference value calculated using the TOPSIS method resulted in the first rank with the highest preference value of 0.78393, followed by GH Supplier with a value of 0.75611, and FR Supplier in third place with a value of 0.6913. The next supplier is Supplier AG with a value of 0.59912, followed by Supplier BR with 0.51682, and Supplier TR in sixth position with 0.465. Supplier IH has a preference value of 0.43166, followed by Supplier YS with a value of 0.3984, and finally Supplier RT is in the lowest position with a value of 0.35517. This ranking shows that US Supplier is the best supplier, while Supplier RT is the lowest choice based on the criteria used.]]>
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