Implementing the SAW Method in a Web-Based Decision Support System for Study Program Selection: Development, Testing, and Evaluation at a Private University in Indonesia - Ahmad Ryadussholihin Syafi’i; Asmaul Husna RS; Sirajun Nasihin; Mindi Richia Putri; M. Dermawan Mulyodiputro (Academic Bright Collaboration, 2026)
Purpose – This study aims to address the problem of inappropriate study program selection among prospective university students by developing a web-based decision support system (DSS) using the Simple Additive Weighting (SAW) method to generate objective and structured recommendations. Methods – The research employs a system development approach by implementing the SAW method in a web-based DSS. The system evaluates four cognitive criteria, namely verbal ability (weight 0.25), numerical ability (weight 0.30), logical reasoning (weight 0.25), and spatial ability (weight 0.20), applied to four D3 study program alternatives. Each criterion was weighted, normalized, and calculated to produce a ranking of study program alternatives. Data were collected through questionnaires and institutional academic records. Findings – A pilot test involving 40 high school students showed an 85% alignment rate, where most participants considered the recommendations appropriate to their interests. User acceptance scores ranged from 4.25 to 4.32 out of 5 across usability, interface clarity, and recommendation usefulness, indicating a positive initial reception. These results suggest the system demonstrates preliminary feasibility as a structured recommendation aid, though broader generalization requires further testing. Research Implications – The findings suggest that multi-criteria DSS can enhance the objectivity and consistency of study program recommendations and can be practically implemented in higher education admission processes. Originality – This study contextualizes the SAW method within a specific private university setting, applying it to four D3 study program alternatives using four cognitive criteria weights established through institutional input. The contribution lies in combining system implementation, functional testing, and user acceptance evaluation into a documented development framework applicable to higher education admission support contexts.