<![CDATA[Securing competent employees who meet an organization’s needs makes the recruitment process a vital part of human resource management. In real world situations, the selection of prospective employees often remains subjective, producing decisions that lack objectivity and quantifiable measures. Hence, a systematic and data driven decision support system becomes necessary. This research aims to create a decision support system for employee recruitment through a hybrid framework that integrates the Analytic Hierarchy Process (AHP) and Weighted Product (WP). Through pairwise comparisons and consistency testing, AHP establishes each criterion’s priority weight. Meanwhile, WP uses those weights to calculate preference values and determine the final ranking of applicants. Based on the AHP calculation results, the criteria weights obtained were work experience (0.30), training certification (0.25), physical health (0.20), communication skills (0.15), and age (0.10) with a Consistency Ratio value of 0.046, indicating a consistent matrix. Furthermore, calculations using the Weighted Product method produced the highest preference value of 0.222 for alternative A5, which is therefore recommended as the best candidate in the employee recruitment process. The research results show that the application of the hybrid AHP and WP method can support the employee recruitment process more objectively and systematically in determining the best candidate. The implementation of this decision support system is expected to help companies improve the quality of decision-making and the efficiency of the employee selection process.]]>
