Article Per Year (5 Year)
p-Index From 2020 - 2025
0.23
P-Index
This Author published in this journals
All Journal Jurnal Tekinkom (Teknik Informasi dan Komputer)
Jefri Syah Putra Laoli
Universitas Prima Indonesia
Computer Science & IT

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
PERBANDINGAN ALGORITMA C5.0 DAN K-MEANS CLUSTERING UNTUK MEMPREDIKSI KEPUASAN MAHASISWA TERHADAP KINERJA DOSEN UNIVERSITAS PRIMA INDONESIA Jefri Syah Putra Laoli; Sadarman Zebua; Novanius Lahagu; Delima Sitanggang; Evta Indra
Jurnal Tekinkom (Teknik Informasi dan Komputer) Vol 6 No 2 (2023)
Publisher : Politeknik Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37600/tekinkom.v6i2.938

Abstract

Data mining is an attempt to dig up valuable and useful information on very large databases. Data mining is an operation that uses certain techniques or methods to look for a pattern or different form in a selected data. The technique used in this study is using data mining with the C5.0 and K-Means methods. The purpose of this study was to determine student satisfaction by using and comparing the accuracy of the C5.0 and K-Means clustering algorithms in predicting student satisfaction on lecturer performance at Universita Prima Indonesia, Faculty of Science and Technology. The results of research using the C5.0 Algorithm method where the accuracy value obtained is 90.90% (Very Satisfied) while the accuracy value is 9.10% (Not Satisfied). The K-Means Clustering method gives quite good results in classifying data, more than 75% of respondents feel (Very Satisfied) while less than 25% feel (Not Satisfied) from the teaching given by lecturers at Universitas Prima Indonesia.
Co-Authors Delima Sitanggang, Delima Evta Indra Novanius Lahagu Sadarman Zebua