Infotekmesin
Vol 15 No 2 (2024): Infotekmesin, Juli 2024

Klustering Data Mahasiswa Menggunakan Metode K-Means Sebagai Acuan dalam Penentuan UKT Mahasiswa

Prasetyanti, Dwi Novia (Unknown)
Riyadi Purwanto (Unknown)
Cahya Vikasari (Unknown)
Rostika Listyaningrum (Unknown)



Article Info

Publish Date
05 Aug 2024

Abstract

Determining Uang Kuliah Tunggal/UKT for new students is important in Penerimaan Mahasiswa Baru/PMB process after PMB selection process. The determination of UKT groups by The PMB committee at Politeknik Negeri Cilacap is carried out one by one by looking at the economic data of new students. This condition has become a special problem due to the increase in PMB quotas in the PNC, so it requires alternative solutions that can be used as one of the benchmarks in the determination of a new student UKT group in PNC. The researchers used clustering with features that represent the economic conditions of new students with the K-means method to provide alternative solutions. The result of using the K-Means method in clustering, yielding a performance value for the number of clusters 8 of 1669,283, with the highest number of cluster members in cluster members in cluster 4 being 72 out of 275 data. The Elbow method test results to determine the best number of clusters resulting in 4 cluster with a performance value of 2462,003.

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Journal Info

Abbrev

infotekmesin

Publisher

Subject

Computer Science & IT Electrical & Electronics Engineering Mechanical Engineering

Description

INFOTEKMESIN is a peer-reviewed open-access journal with e-ISSN 2685-9858 and p-ISSN: 2087-1627 published by Pusat Penelitian dan Pengabdian Masyarakat (P3M) Politeknik Negeri Cilacap. The journal invites scientists and engineers to exchange and disseminate theoretical and practice-oriented in the ...