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Aryanti Mita
STMIK Bandung
Computer Science & IT Decision Sciences, Operations Research & Management Education Engineering Library & Information Science

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EVALUASI KINERJA AKADEMIK MAHASISWA MENGGUNAKAN ALGORITMA K-MEANS CLUSTERING Rini Nuraini Sukmana; Aryanti Mita; Abdurrahman Abdurrahman
JURTIK:Jurnal Penelitian dan Pengembangan Teknologi Informasi dan Komunikasi Vol 8 No 1 (2019): JURTIK : Jurnal Teknologi Informasi dan Komunikasi
Publisher : LPPM STMIK BANDUNG

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (499.206 KB) | DOI: 10.58761/jurtikstmikbandung.v8i1.125

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
Co-Authors Abdurrahman Rini Nuraini Sukmana