<![CDATA[The promotion selection process within an organization is a crucial aspect that influences long-term performance and success. Proper selection can enhance employee motivation and productivity; however, traditional subjective methods often lead to bias and unfairness in the selection process. This study aims to develop a Decision Support System (DSS) for promotion selection using the Rank Sum and Additive Ratio Assessment (ARAS) methods to support more objective and structured decision-making. The Rank Sum method is used to objectively determine the weight of criteria based on their order of importance, while the ARAS method is employed to evaluate and rank alternatives based on various predetermined criteria. The combination of these two methods is expected to provide more accurate and transparent assessments of promotion candidates. The results of the study indicate that the developed DSS can provide the best alternative recommendations through ranking the relative performance values from highest to lowest. The case study shows that the highest utility value is Ahmad Nazir (A3) with a score of 0.9346, followed by Ricky Hamdani (A4) with a score of 0.9142, Andy Setiawan (A1) with a score of 0.8769, and Tati Maharani (A2) with a score of 0.8659. The consistency between the system output and manual calculations demonstrates the validity of the system results, while black box testing ensures that all main features function as expected.]]>
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