Jurnal Tekinkom (Teknik Informasi dan Komputer)
Vol 4 No 2 (2021)

PENERAPAN DATA MINING PADA PENERIMAAN MAHASISWA BARU DENGAN ALGORITMA K-MEANS CLUSTERING

Septian Isnanto (UniversitaS Gunadarma)
Suryarini Widodo (Unknown)



Article Info

Publish Date
30 Dec 2021

Abstract

This paper aims to grouping data using Clustering method with k-means algorithm to find potential majors and type of schools that produce feature students who have a good GPA score in semester 1 and semester 2 at Politeknik STMI Jakarta. Dataset from academic data for 2017-2020 has been processed with Rapid Miner showing that in Automotive Business Administration study program there are 3 clusters of students where cluster 0 marked as best cluster is dominated by high school students majoring in Science and Social Sciences. Automotive Industry Information System study program produces 2 clusters of students where cluster 0 marked as best cluster is dominated by high school students majoring in science and vocational high school majoring in mechanical engineering. Automotive Industrial Engineering study program produces 2 clusters of students where cluster 1 marked as best cluster is dominated by high school students majoring in science. Polymer Chemical Engineering study program produces 6 student clusters where cluster 4 marked as best cluster which all come from high school students majoring in science.

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Journal Info

Abbrev

Tekinkom

Publisher

Subject

Computer Science & IT

Description

Jurnal TEKINKOM merupakan jurnal yang dimaksudkan sebagai media terbitan kajian ilmiah hasil penelitian, pemikiran dan kajian analisis-kritis mengenai isu Ilmu - ilmu komputer dan sistem informasi, seperti : Pemrograman Jaringan, Jaringan Komputer, Teknik Komputer, Ilmu Komputer/Informatika, Sistem ...