Application of K-Means Algorithm for Clustering the Quality of Lecturer Learning at Batam International University

Yefta Christian (Universitas Internasional Batam, Kepulauan Riau, Indonesia)

IJISTECH
Vol 3, No 2 (2020): May

The need to measure the quality of learning becomes very significant when the quality of learning is still low. This also applies to the quality of learning at the highest level. The quality of lecturer learning in class is often not in accordance with what it should be, one of the constraints of this low quality is that the quality of lecturer learning is not accurately measured. Data mining is used in this research to map the quality of lecturer learning based on its cluster, namely Clustering, It is hoped that universities can measure the quality of learning from their lecturers accurately. From this research, students with low social studies tend to value lecturers with low grades; conversely students with high social studies tend to judge lecturers with high enough grades. The k-Means algorithm is accurate enough to be used in clustering the quality of lecturer learning based on grades and results of student questionnaires.