EVALUASI KINERJA AKADEMIK MAHASISWA MENGGUNAKAN ALGORITMA K-MEANS CLUSTERING

Authors

  • Rini Nuraini Sukmana STMIK Bandung
  • Aryanti Mita STMIK Bandung
  • Abdurrahman Abdurrahman STMIK Bandung

Keywords:

k-means clustering, k-means implementation, student Academic Insurance

Abstract

One indicator of higher education that is able to compete can be seen from the success of students from these universities in taking their studies. The success of a student can be seen from the achievement index he achieve.Many factors are a barrier for students to achieve and maintain a high achievement index that reflects their overall efforts during college. These factors can be targeted by universities as an action to develop strategies to improve student achievement and improve academic performance by monitoring the progress of their performance.In this study a system has been developed that can function to classify student academic performance to facilitate the study program section in monitoring student grades.
Clustering is one of the most important research fields in the field of data mining. Clustering is the process of classifying or classifying objects based on information obtained from data that explains the relationship between objects with the principle of maximizing similarity between members of one cluster and minimizing similarities between clusters. This introduces the concept of the K-Means Algorithm and describes how this concept can be applied by academic actors to evaluate student academic performance

Published

2019-06-01

How to Cite

Sukmana, R. N., Mita, A., & Abdurrahman, A. (2019). EVALUASI KINERJA AKADEMIK MAHASISWA MENGGUNAKAN ALGORITMA K-MEANS CLUSTERING. Jurnal Teknologi Informasi Dan Komunikasi, 8(1), 11–15. Retrieved from http://journal.stmik-bandung.ac.id/index.php/JurnalTI/article/view/125

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