Clusterization Using K-Means Clustering Algorithm In Predicting Student Graduation Time

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Published: Aug 30, 2021
Keywords:
Data Mining, K-Means Clustering, Predicting Student Graduation
Issue
Vol. 5 No. 2 (2021): Augustus: Manajemen, Teknologi Informatika dan Komunikasi (Mantik)
Section
Computer Science
Statistics Article
Article View : 91 Times

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Syaiful Zuhri Harahap
Labuhanbatu University
Masrizal
Labuhanbatu University

Abstract

Education at the college level is a suggestion that students can get a degree in order to have knowledge in the field of computer science. Taking a decision from a BIG DATA for Predicting student graduation time is useful to provide a means of knowing the estimated time of a student's graduation by seeing which students fall into a certain cluster based on the parameters of the Cumulative Achievement Index (GPA) and attendance. It is hoped that it can help the campus and students to predict the graduation rate on time and to improve the reputation for the campus itself and timely graduation for students so that their graduation is not late, besides that the campus can do things that need to be done if they are predicted pass not on time like by making motivation and other things.

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How to Cite
Harahap, S. Z. and Masrizal (2021) “Clusterization Using K-Means Clustering Algorithm In Predicting Student Graduation Time”, Jurnal Mantik, 5(2), pp. 1424-1428. Available at: https://iocscience.org/ejournal/index.php/mantik/article/view/1588 (Accessed: 10June2026).
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