IMPLEMENTASI K-MEANS UNTUK CLUSTERING KEPUASAN MAHASISWA TEKNIK INFORMATIKA TERHADAP LAYANAN AKADEMIK

Abstract

Student satisfaction with academic services is important for universities. This research aims to trigger student satisfaction with academic services by using the clustering data mining method, namely the K-Means algorithm. The data used in this research are the results of a questionnaire on student satisfaction with academic services for the 2022/2023 even semester academic year at the Muhammadiyah University of East Kalimantan, with a total of 662 students. The research results show that the majority of students are satisfied with academic services with a percentage of 60%, followed by very satisfied at 35%, quite satisfied at 4%, and less satisfied at 1%. This shows that student satisfaction with academic services at Muhammadiyah University of East Kalimantan is very high. Based on the research results, academics can think about aspects of academic services that still need to be improved, namely aspects of service compassion, limited service time, and availability of facilities and infrastructure. By evaluating and improving these aspects, it is hoped that student satisfaction with academic services at Muhammadiyah University of East Kalimantan can continue to increase.