Article Per Year (5 Year)
p-Index From 2019 - 2024
0.408
P-Index
This Author published in this journals
All Journal IJISTECH (International Journal Of Information System & Technology) IJISTECH
Yefta Christian
Universitas Internasional Batam, Kepulauan Riau, Indonesia
Computer Science & IT Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Engineering Social Sciences

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
Application of K-Means Algorithm for Clustering the Quality of Lecturer Learning at Batam International University Yefta Christian
IJISTECH (International Journal of Information System and Technology) Vol 3, No 2 (2020): May
Publisher : Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/ijistech.v3i2.49

Abstract

The need to measure the quality of learning becomes very significant when the quality of learning is still low. This also applies to the quality of learning at the highest level. The quality of lecturer learning in class is often not in accordance with what it should be, one of the constraints of this low quality is that the quality of lecturer learning is not accurately measured. Data mining is used in this research to map the quality of lecturer learning based on its cluster, namely Clustering, It is hoped that universities can measure the quality of learning from their lecturers accurately. From this research, students with low social studies tend to value lecturers with low grades; conversely students with high social studies tend to judge lecturers with high enough grades. The k-Means algorithm is accurate enough to be used in clustering the quality of lecturer learning based on grades and results of student questionnaires.
Application of K-Means Algorithm for Clustering the Quality of Lecturer Learning at Batam International University Yefta Christian
IJISTECH (International Journal of Information System and Technology) Vol 3, No 2 (2020): May
Publisher : Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1041.433 KB) | DOI: 10.30645/ijistech.v3i2.49

Abstract

The need to measure the quality of learning becomes very significant when the quality of learning is still low. This also applies to the quality of learning at the highest level. The quality of lecturer learning in class is often not in accordance with what it should be, one of the constraints of this low quality is that the quality of lecturer learning is not accurately measured. Data mining is used in this research to map the quality of lecturer learning based on its cluster, namely Clustering, It is hoped that universities can measure the quality of learning from their lecturers accurately. From this research, students with low social studies tend to value lecturers with low grades; conversely students with high social studies tend to judge lecturers with high enough grades. The k-Means algorithm is accurate enough to be used in clustering the quality of lecturer learning based on grades and results of student questionnaires.
Co-Authors