Implementation of a Decision Support System Based on the Simple Additive Weighting (SAW) Method and Apriori Algorithm for Student Achievement Evaluation

Abstract

This study aims to develop and implement a Decision Support System (DSS) to assess student achievement using the Simple Additive Weighting (SAW) method, complemented by the Apriori algorithm as a validation tool. The system evaluates students based on five criteria: academic performance, attendance, championships, discipline, and activeness. The SAW method is used to calculate preference scores and rank students objectively and systematically, while Apriori identifies frequently occurring transaction patterns and validates the consistency of new student data against the training dataset. Test results show that both SAW and Apriori achieved an accuracy of 87% compared to manual calculations, indicating that the combination of these two methods can provide consistent and reliable decisions.