Amrullah Amrullah
STMIK Lombok, Indonesia

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Implementation of the Weighted Product Method in Decision Support Systems Selection of Outstanding Students Harun Arrosyid; Sofiansyah Fadli; Amrullah Amrullah
Journal of Intelligent Decision Support System (IDSS) Vol 9 No 2 (2026): June: Intelligent Decision Support System (IDSS)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/idss.v9i2.363

Abstract

The selection of outstanding students is an important process in education as it serves as the basis for awarding achievements and motivating students to improve both their academic and non-academic performance. However, the selection process in many schools is still carried out manually, which may lead to subjectivity and a lack of transparency in decision-making. This issue also occurs at SMA Plus Nurul Mubin, creating the need for a Decision Support System (DSS) that can assist the evaluation process in a more objective and systematic manner. This study aims to implement the Weighted Product (WP) method to determine outstanding students based on four criteria: Subject Grades, discipline, attendance, and extracurricular participation. The weight assigned to each criterion was determined based on the school's policies as the basis for the decision-making process. The research employed data collection methods including interviews, observations, and documentation. The collected data were then processed using the Weighted Product (WP) method through weight normalization, vector S calculation, and vector V calculation to obtain the final ranking results. The findings indicate that the Weighted Product (WP) method is capable of providing objective recommendations for outstanding students based on the preference value of each alternative. Based on the calculation results, alternative S3 obtained the highest vector V value of 0.176193538, ranking first as the outstanding student. It was followed by S6 with a value of 0.170283200, S5 with 0.168336098, S2 with 0.166745623, S1 with 0.160578981, and S4 with 0.157862560. These results demonstrate that the Weighted Product (WP) method is capable of producing an objective, effective, and transparent ranking of students based on the predetermined criteria weights. Therefore, the developed system can serve as a recommendation tool for schools to support the outstanding student selection process in a more accurate, structured, and accountable manner