<![CDATA[The selection of thesis supervisors is a crucial process in higher education but is often conducted manually and subjectively, leading to mismatches in expertise, unequal workload distribution, and inefficiencies. This study aims to develop a decision support system (DSS) to assign thesis supervisors objectively and fairly. The approach combines the Entropy and TOPSIS methods. The Entropy method is used to calculate objective weights for five criteria: academic rank, field of expertise, student preference, supervision quota, and student graduation speed. The TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) method is then applied to rank supervisor candidates based on their proximity to ideal solutions. The results demonstrate that the system effectively recommends the most suitable supervisor, with Lecturer G identified as the top choice. This system is expected to enhance the efficiency, transparency, and equity of the thesis supervisor assignment process within the Informatics Engineering Program at Malikussaleh University.]]>
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