Article Per Year (5 Year)
p-Index From 2021 - 2026
0.23
P-Index
This Author published in this journals
All Journal Computing and Information System Journal
Ali Afendi
Universitas Muhammadiyah Jember
Computer Science & IT

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

Found 1 Documents
Search

 1 
Clustering of Lecturer Performance Based on Internal Data and Questionnaire Using the X-Means Algorithm Ali Afendi; Rosita Yanuarti; Qurrota A’yun
Computing and Information System Journal Vol. 2 No. 1 (2026): Inovasi Teknologi Cerdas Berbasis AI, IoT, dan Data Mining di Era Digital
Publisher : IndoCompt Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Lecturer performance evaluation is essential for improving the quality of higher education. In the Informatics Engineering Study Program at Universitas Muhammadiyah Jember, assessments are still conducted manually, leading to inefficiency and subjectivity. This study aims to cluster lecturer performance based on internal data—credit load, publications, attendance, and students’ average grades—and student perceptions collected through questionnaires, using the X-Means Clustering algorithm. X-Means was chosen because it can automatically determine the optimal number of clusters using the Bayesian Information Criterion (BIC) and log-likelihood. The research involved data collection, cleaning, normalization with the Min-Max method, implementation of X-Means, and visualization using Principal Component Analysis (PCA). The results identified five distinct clusters: high-performing lecturers, lecturers with high publication output, research-active lecturers with low student grades, low-performing lecturers, and stable-performing lecturers. These findings provide an objective view of lecturer performance variations and can serve as a basis for developing effective strategies for lecturer improvement and continuous performance evaluation
Co-Authors Qurrota A’yun Yanuarti, Rosita