Optimizing the Selection of Outstanding Students Using the Weighted Product (WP) Method in a Web-Based Decision Support System

Abstract

Students as learning agents and seekers of knowledge need to be encouraged to explore their potential, including in aspects of hard skills and soft skills. This research focuses on building a Decision Support System (SPK) with the Weighted Product (WP) method to determine the best students. Improving students' future existence depends not only on the excellence of hard skills, but also the balance of soft skills. The research involved four journals related to SPK student selection, and WP was chosen as an evaluation method. The research process begins with literature collection and system design, including design procedures, system usage, relationships between tables, use case diagrams, and WP method flowcharts. The implementation of the system includes a login page, input of criteria and alternative values, and the process of calculating student rankings. WP gives an accurate ranking, with Alternative 9 (Rifai) as the best student. Testing shows a high degree of accuracy between manual results and system results. This DSS provides an objective evaluation of student achievement, with the potential for further development related to data integration with academic systems and user interface improvement. The conclusion of this study is that SPK with the WP method can provide student rankings efficiently and accurately, helping to support decision making related to the selection of the best students. Further development suggestions involve feature enhancements, data maintenance, and further integration with academic systems to improve system reliability.

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