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All Journal "Journal of Data Science
Einson O.B Nainggolan
Universitas Katolik Santo Thomas Medan, Fakultas Ilmu Komputer
Automotive Engineering Computer Science & IT

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K-Means Clustering of Student Mid-Term and Final Exam Score Data Nella Ane Br Sitepu; Agnesia Rointan Sijabat; Cindy Rounali Limbong; Lenny Evalina Pasaribu; Einson O.B Nainggolan; Michael Manulang
Journal Of Data Science Vol. 2 No. 02 (2024): Journal Of Data Science, September 2024
Publisher : Sean Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58471/jds.v2i02.5417

Abstract

Clustering is a method in data mining that aims to group data based on similar characteristics. This research utilises the k-means clustering algorithm to group students based on their UTS and UAS scores, making it easier for lecturers to identify students' academic abilities. With the application of this method, it is expected to form groups of students who are intelligent, less intelligent, and moderate. In addition, this research also addresses the challenges in observing student grades which are often done manually, resulting in wasted time and effort. Through the k-means clustering approach, this research aims to improve the quality of education by providing insight for education managers in mapping student learning outcomes. The k-means method used includes determining the cluster centre point and calculating the distance between data, which is repeated until convergence is achieved. The results show that this method is effective in identifying student achievement patterns, providing a basis for decision-making to improve academic achievement in higher education.
Co-Authors Agnesia Rointan Sijabat Cindy Rounali Limbong Lenny Evalina Pasaribu Michael Manulang Nella Ane Br Sitepu