Segmentasi Minat Mahasiswa Terhadap Program Studi Menggunakan Algoritma K-Means Clustering

Wahyudin, Edi
Dikananda, Fatihanursari

BULLET : Jurnal Multidisiplin Ilmu
Vol. 2 No. 1 (2023): BULLET : Jurnal Multidisiplin Ilmu

Segmenting student interest in study programs is a crucial step in strategic decision-making within higher education. By identifying interest groups, institutions can design more relevant curricula and develop more effective marketing strategies. This study aims to cluster student interests in study programs using the K-Means Clustering algorithm. The data used in this research were obtained from questionnaires assessing the interests and preferences of new students towards various study programs. The results of applying the K-Means algorithm indicate that students can be grouped into several clusters based on the similarity of their interests, which can be utilized to support academic policy and program promotion strategies.