K-Medoids Algorithm Analysis in Grouping Students' Level of Understanding of Subjects

Ehrlich F.T  Butarbutar; M.  Safii

doi:10.59934/jaiea.v1i1.50

Authors

Ehrlich F.T Butarbutar STIKOM Tunas Bangsa Pematangsiantar, Sumatera Utara
M. Safii AMIK Tunas Bangsa Pematangsiantar, Sumatera Utara

DOI:

https://doi.org/10.59934/jaiea.v1i1.50

Keywords:

Understanding of the material, Feedback, Data mining, Clustering, K-Medoids algorithm

Abstract

Analysis of the teaching and learning process needs to be done as feedback on the understanding of the material for students. One of the obstacles faced by schools is that there is no method of how this feedback can be done so that student achievement is uneven. Student achievement in subjects can be seen from the results of the scores on the report cards obtained by students after taking the final semester exam. Due to the uneven achievement of students, it is necessary to make a method so that feedback analysis can be carried out on the level of student understanding of the subject. Is data mining with clustering techniques using the K-Medoids algorithm. With this algorithm, students' understanding of subjects with high potential can be grouped with high brightness average results

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