A Hybrid SITDE Weighting and HYBSO Method in Decision Support Systems for Warehouse Employee Selection - Tri Widodo; Okma Arnilia; Iryanto Chandra; Sahrial Ihsani Ishak; Setiawansyah Setiawansyah (Journal of Artificial Intelligence and Technology Information (JAITI), 2026)
Warehouse employee selection is a complex process because it involves various heterogeneous criteria, both quantitative and qualitative, such as physical tests, accuracy, work experience, discipline, and teamwork ability. A selection process that still relies on subjective judgment risks producing inconsistent and suboptimal decisions. This study proposes a hybrid method that integrates skewness impact through distributional evaluation (SITDE) for objective determination of criteria weights with a hybrid solution algorithm (HYBSO) for systematic ranking of alternatives. The results of applying this method indicate that Work Experience has the highest weight of 0.2813, followed by the Discipline Test (0.1969) and Physical Test (0.1926), while the Accuracy Test (0.1641) and Teamwork Test (0.1652) have lower weights. The final ranking results show that Candidate HW ranks first with a score of 0.3596, followed by Candidate FN (0.7066) and Candidate DK (0.9162). The sensitivity analysis evaluates the stability of the ranking results under changes in criterion weights across 20 scenarios, demonstrating the robustness of the proposed SITDE-HYBSO method and identifying candidates whose ranking positions are more sensitive to variations in criterion importance. These findings confirm that the SITDE-HYBSO hybrid method is capable of producing objective, consistent, and accountable employee selection decisions, while also providing an adaptive mechanism to respond to changes in organizational priorities.