<![CDATA[The selection of thesis examiners is a crucial process for student academic success, yet it is often based on unstructured subjective considerations. This study aims to address this issue by designing and implementing a Decision Support System (DSS) to provide objective lecturer recommendations. The system integrates the Analytical Hierarchy Process (AHP) method for consistent criteria weighting and the Simple Additive Weighting (SAW) method to rank 10 lecturer alternatives based on four main criteria: Academic Qualification (K1), Time Availability (K2), Total Guidance (K3), and Structural Position Workload (K4). The AHP analysis results indicate that Academic Qualification (K1) is the highest priority criterion with a weight of 0.449 and a highly valid consistency ratio (CR = 0.04). Subsequently, the SAW calculation yielded three candidates who ranked at the top with a maximum preference score of 1.000. This study concludes that the hybrid AHP-SAW model provides an objective, transparent, and efficient framework for the lecturer selection process, successfully delivering accountable recommendations to assist decision-making within the academic environment.]]>
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