Subject Selection Decision Support System Using the Weighted Aggregated Sum Product Assessment Method

Abstract

High school subject selection is crucial for aligning with students' interests and goals, but manual processes are often time-consuming and prone to errors. This study developed a decision support system using the WASPAS method, which combines WSM and WPM to produce a more stable and consistent evaluation of alternatives. A total of 35 10th-grade students of SMAN 16 Medan were recruited through total sampling using a Likert-scale questionnaire as the basis for the calculation. The system evaluation was verified on the entire data set, not just three samples like the previous version, to ensure the algorithm's suitability. The results show that the system generates interest recommendations based on the highest Qi score and is consistent with manual calculations, although its accuracy cannot yet be fully concluded. The distribution of student preferences is also presented, along with explanations of potential instrument bias and response bias as limitations of the study. Overall, this WASPAS-based system is considered capable of helping provide more objective and efficient subject selection recommendations.