Integration of AHP and TOPSIS Methods in Decision Making Models to Identify High Achieving Students

Abstract

Selection of outstanding students is an essential process in education to ensure that students with high achievements receive appropriate recognition and guidance. However, this process often suffers from subjectivity and the absence of a structured decision-making system. This study aims to develop an objective and accountable decision support model by integrating the Analytic Hierarchy Process (AHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) methods. The AHP method is used to determine the weight of each selection criterion, while the TOPSIS method is used to rank students based on their proximity to the ideal solution. The study involved 10 student candidates and assessed them based on 6 criteria, including academic performance, discipline, extracurricular activities, and religious values. The results show that the integrated AHP-TOPSIS model successfully identifies students with the highest preference values as the most outstanding, while those with lower values are recommended for further coaching. The model demonstrates its effectiveness in supporting accurate, data-driven student selection at MIMA 37 Sunan Kalijogo Ambulu.