Clustering Data Penerimaan Mahasiswa Baru Universitas Handayani Makassar Menggunakan Algoritma K-Means

A. Ade Rosali Saputra
Samsart Deandi Palumery
Hazriani, Hazriani
Yuyun, Yuyun

Prosiding Seminar Nasional Sisfotek (Sistem Informasi dan Teknologi Informasi)
Vol 7 No 1 (2023): SISFOTEK VII 2023

This research aims to group new student data for the 2022 academic year at Handayani University Makassar by utilizing a data mining process using the K-Means Clustering algorithm. Implementation using Rapidminer software is used to help determine accurate values. The data used in carrying out this research consists of 4 (four) attributes, namely, school origin, average UAS (final semester exam) score, gender and chosen study program. The research process begins by selecting data and then transforming the data into a numerical group. It is hoped that the results of this research can help universities in improving appropriate promotional strategies in each study program at Handayani University, Makassar.