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All Journal Techno Nusa Mandiri : Journal of Computing and Information Technology Jurnal Computer Science and Information Technology (CoSciTech) jeti Jurnal Sisfotek Global
Cut Lika Mestika Sandy
universitas islam kebangsaan indonesia
Computer Science & IT Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering

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Journal : jeti

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Implementasi Metode K-Means Dalam Menentukan Mahasiswa Potensial Drop Out Cut Lika Mestika Sandy
Jurnal Elektronika dan Teknologi Informasi Vol 3 No 2 (2022): September 2022
Publisher : LPPM-UNIKI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5201/jet.v3i2.288

Abstract

Data mining is a process to find the pattern or interesting piece of information in selected data using the technique or certain methods. Techniques, the method or algorithm in data mining varies. In this research, the data mining is used to determine potential students drop out with using logarithm K-means. This system groups students at the Informatics of Engineering at University Islam Kebangsaan Indonesian, A generation 2019 until 2022. Data that are grouped into is the GPA (Grade Point Average) and the number of credits. That is needed by majors at the Informatics of Engineering at University Islam Kebangsaan Indonesian. Results from the system was a student groups critical market drop out. This system is expected to be able to help the way to know more students early critical market drop out and can take action to anticipate it. Keywords: Data Mining, Algorithm K-means, Drop out
Co-Authors Ajulio Padly Sembiring Asmaul Husna Fadlisyah Fadlisyah Muhathir, Muhathir Ona Rizal Fahmi Reyhan Achmad Rizal Taufik Ismail Simanjuntak