Implementasi Metode Simple Additive Weighting pada Sistem Pendukung Keputusan Deteksi Dini Mahasiswa Beresiko Drop Out - Putu Andhika Kurniawijaya; I Wayan Widi Karsana (Jurnal Teknik Informatika dan Teknologi Informasi, 2026)
This researchaims to develop a Decision Support System (DSS) based on theSimple Additive Weighting (SAW) method to detect students who are at risk of dropping out early. The problem of high dropout rates in higher education is often caused by delays in identifying student swho are at academic risk, so a system is needed that is capable ofobjective, rapid, and structured assessment. The study uses five main criteria, namely the number of failed credits, academic leave/inactive status,frequency of late payments, GPA, and remaining study period. Student data is processed through the SAW stages, starting from the formation of a decision matrix,normalization, to the calculation of preference values to determine the drop out risk ranking DO risk. The implementation results show that the system is capable of producing calculations that are fully consistent with manual calculations, thusproving the accuracy and validity of the system's calculation process. This systemis expected to assist academic staff in early detection, so that interventions for at-risk students can be carried out more quickly and effectively.