<![CDATA[The teaching profession holds a strategic role in advancing knowledge and fostering student development. Budi Darma University, as one of the higher education institutions, strives to provide recognition to the best non-computer lecturers, evaluated through measurable criteria such as competence, research output, achievements, educational background, and disciplinary records. However, the similarity of qualifications among lecturers often creates challenges in conducting fair and accurate selection. Therefore, this study applies a Decision Support System (DSS) using the Multi-Objective Optimization on the Basis of Ratio Analysis (MOORA) method to assist decision-making in selecting the best non-computer lecturer. The research involved seven lecturers as alternatives and six assessment criteria, with weights determined using the Rank Order Centroid (ROC) method. The process included defining alternatives, weighting criteria, normalizing the decision matrix, and calculating MOORA optimization values. The results show that alternative A1, namely Suginam, obtained the highest optimization score of 0.6211, and was therefore designated as the best non-computer lecturer. These findings highlight that the MOORA method can provide objective, transparent, and systematic selection results in decision-making processes. Furthermore, this study demonstrates the flexibility of the MOORA method to be adapted to various selection needs in academic settings, particularly in improving lecturer quality and motivation through performance-based recognition.]]>
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