Application of the TOPSIS Method in a Decision Support System for Selecting Scholarship Recipients from Low-Income Backgrounds at Higher Education Institutions

Data Mining

Abstract

Providing scholarships to underprivileged students is a strategic step to increase access to higher education. However, in its implementation, the selection process often encounters obstacles, such as subjectivity in assessments and a high number of applicants. This study aims to design a Decision Support System (DSS) to determine scholarship recipients using the Technique for Order Preference by Similarity to the Ideal Solution (TOPSIS) method. This method was chosen because it is able to produce alternative rankings based on their proximity to the positive ideal solution and their distance from the negative ideal solution. The criteria used include parental income (C1), number of dependents (C2), Grade Point Average (GPA) (C3), monthly family expenses (C4), and housing conditions or residence status (C5). The alternatives implemented consisted of 20 students who had met the administrative requirements. The data processing process was carried out through several stages, namely normalizing the decision matrix, assigning weights to the criteria, determining the ideal solution, and calculating preference values ​​to obtain the final ranking. The results of the study indicate that the TOPSIS method is able to produce a more objective, systematic, and transparent selection process. Therefore, this SPK is expected to assist higher education institutions in more precisely targeting scholarship recipients according to established criteria.