Segmentasi Kinerja Akademik Mahasiswa Menggunakan Algoritma K-Means

Abstract

With the abundance of universities scattered across various regions in the country, they should be able to shape human characteristics and improve the quality of education in Indonesia. Sapta Mandiri Institute of Technology is a private higher education institution Where in learning it is required to be more innovative and creative in producing graduates and responsive to workforce needs. In this study, a group of high- and low-achieving students was carried out with the aim of classifying student efficiency and performance. By combining two techniques, namely the k-means algorithm and elbow clustering, so that the performance results will be more accurate in analyzing and evaluating the progress of student performance. The results show that the application of the Elbow method in this study produces the best number of clusters into 3 clusters. The results of this cluster are useful for the program in analyzing student academic performance based on the cluster formed.