Stream Clustering for Selection Recommendations Using K-Means Algorithm: A Case Study in the Informatics Study Program

  • Riska Fahmita Anggraini Universitas Bina Darma, Indonesia
  • Siti Sau'da Universitas Bina Darma, Indonesia
DOI: 10.51519/journalisi.v5i4.576
Keywords: Software, MK-Stream, K-Means, Clustering, Data Analytic

Abstract

Concentration Stream for a major is a process where students focus their attention on a specific discipline according to their interests. The purpose of specialization is to better orient students to the knowledge they have gained from previous courses, so that they can have a clearer focus. In the Informatics Engineering study program at Bina Darma University there are 3 concentrations, namely: Software Engineering, Network Engineering, Data Analytics. The absence of a system that helps students choose a major concentration makes it quite difficult for students to know their academic abilities. By looking at these problems, this research aims to build a Recommendation system for selecting Mk-Stream Concentrations using the K-Means grouping approach using the K-Means cluster method. Where student academic achievement data from the first semester to the 4th semester is used as a variable in the calculations.

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Published
2023-12-01
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How to Cite
Anggraini, R., & Sau’da, S. (2023). Stream Clustering for Selection Recommendations Using K-Means Algorithm: A Case Study in the Informatics Study Program. Journal of Information Systems and Informatics, 5(4), 1274-1287. https://doi.org/10.51519/journalisi.v5i4.576
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Vol 5 No 4 (2023): Journal of Information Systems and Informatics
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Articles

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