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Abstract
The selection of recipients of the Single Tuition Fee (UKT) assistance at universities must be carried out with the principles of fairness, openness, and efficiency to ensure that the assistance is distributed appropriately. However, the manual selection process is often subjective and prone to error. Therefore, this study developed a decision support system based on the Simple Additive Weighting (SAW) method to assist the selection process of students eligible for UKT assistance more systematically and accurately. The SAW method was chosen because of its ability to process data involving various criteria to produce objective decisions. In this study, the criteria used for the selection of UKT assistance recipients include several aspects, such as the Cumulative Grade Point Average (GPA), parental income, number of dependents, non-academic achievements, distance of the student's residence from campus, active student status, and involvement in student organizations. Data from each criterion is then processed through a normalization stage to ensure uniformity of values and weighting based on their level of importance. After the normalization and weighting process, the next step is to calculate the preference value for each student. The results of the implementation of this system show that the SAW method can accurately rank student priorities, with a student named Selly receiving the highest preference score, 0.673. This indicates that the student in question meets the selection criteria with the best score. This developed system can support the UKT assistance selection process to be fairer and more efficient. By using the SAW method, subjective and manual errors in decision-making can be reduced, resulting in more objective and accurate decisions. In addition, this system also allows universities to evaluate UKT assistance recipients more transparently and precisely, which ultimately can increase public trust in the management of educational assistance at universities.