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

Authors

  • Syaiful Zuhri Harahap Universitas Labuhanbatu
  • Masrizal Universitas Labuhanbatu

DOI:

https://doi.org/10.52218/ijbtob.v1i6.152

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

Downloads

Download data is not yet available.

References

A. P. Narendra, (2015). Data Besar, Data Analisis, dan Pengembangan Kompetensi Pustakawan,” Rec. Libr. J., vol. 1, no. 2, pp. 83–93.

F. Nur, M. Zarlis, and B. B. Nasution (2015) Penerapan Algoritma K-Means Pada Siswa Baru Sekolahmenengah Kejuruan Untuk Clustering Jurusan, InfoTekJar J. Nas. Inform. dan Teknol. Jar., vol. 1, no. 2, pp. 100–105.

Gustientiedinaa, M. H. Adiyaa, and Y. Desnelitab (2019) Penerapan Algoritma K-Means Untuk Clustering Data Obat-Obatan Pada RSUD Pekanbaru,” J. Nas. Teknol. dan Sist. Inf. Univ. Andalas, vol. 5, no. 1, pp. 17–24.

H. Priyatman, F. Sajid, and D. Haldivany (2019). Klasterisasi Menggunakan Algoritma K-Means Clustering untuk Memprediksi Waktu Kelulusan,” JEPIN (Jurnal Edukasi dan Penelit. Inform., vol. 5, no. 1, pp. 62–66.

M. Linda, (2018). Penerapan Datamining Dalam Mengelompokkan Kunjungan Wisatawan Ke Objek Wisata Unggulan Di Prov . Dki Jakarta Dengan K-Means,” Jiska (Jurnal Inform. Sunan Kalijaga), vol. 2, no. 3, pp. 167–174.

Muliono R, Sembiring Z (2019). Data Mining Clustering Menggunakan Algoritma K-Means Untuk Klasterisasi Tingkat Tridarma Pengajaran Dosen," Cess (Journal of Computer Engineering System and Science), vol 4, no 2.

R. P. S. Putri and I. Waspada (2018). Penerapan Algoritma C4.5 pada Aplikasi Prediksi Kelulusan Mahasiswa Prodi Informatika,” Khazanah Inform. J. Ilmu Komput. dan Inform., vol. 4, no. 1, pp. 1–7.

Sari V. N, Yupianti, Maharani D (2018). Penerapan Metode K-Means Clustering Dalam Menentukan Predikat Kelulusan Mahasiswa Untuk Menganalisa Kualitas Lulusan, “ JURTEKSI (Jurnal Teknologi dan Sistem Informasi) vol 4. no 2. pp 133-140.

T. Rismawan and S. Kusumadewi (2008). Aplikasi K-Means Untuk Pengelompokkan Mahasiswa Berdasarkan Nilai Body Mass Index (Bmi) & Ukuran Kerangka,” Proc. Semin. Nas. Apl. Teknol. Inf., vol. 1, no. 1, pp. 43–48.

Downloads

Published

09-12-2021

How to Cite

Syaiful Zuhri Harahap, & Masrizal. (2021). Clusterization Using K-Means Clustering Algorithm In Predicting Student Graduation Time. International Journal of Business, Technology and Organizational Behavior (IJBTOB), 1(6), 484–489. https://doi.org/10.52218/ijbtob.v1i6.152