Sistem Pendukung Keputusan Rekomendasi Organisasi Untuk Mahasiswa di Universitas Bina Darma Menggunakan Metode Simple Additive Weighting (SAW)

Jurnal Informatika Dan Tekonologi Komputer
Vol. 5 No. 3 (2025): November : Jurnal Informatika dan Tekonologi Komputer

This research was conducted to develop a web-based Decision Support System (DSS) to provide student organization recommendations at Universitas Bina Darma. The Simple Additive Weighting (SAW) method was used to evaluate compatibility based on students’ interests, talents, and preferences. The K-Nearest Neighbor (KNN) algorithm was applied to classify the SAW score results in order to determine the final recommendation. In line with its domain, the system was developed using an Agile Feature-Driven Development (FDD) approach in a gradual and iterative manner, utilizing the Laravel 12 framework. The research results showed that the system was capable of accurately recommending Student Activity Units (UKM) for first- to fourthsemester students. The recommendation process was carried out by combining the SAW method to obtain the top three UKM and the KNN algorithm for final classification when students chose to participate in only one UKM that best matched their historical answer patterns.