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Urrohman, Maysas Yafi
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Computer Science & IT

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Clustering of Lecturer Performance Using K-Means Rouf, Abdur; Qoritunnadyah, Marita; Asyari, Hasyim; Urrohman, Maysas Yafi
Journal of Informatics Development Vol. 3 No. 1 (2024): Oktober 2024
Publisher : Institut Teknologi dan Bisnis Widya Gama Lumajang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30741/jid.v3i1.1430

Abstract

Lecturers serve as professional educators and scientists whose primary roles are knowledge transformation, development, and dissemination in fields such as science, technology, and the arts through education, research, and community service. They play a critical role in fostering an educated generation, and as such, must maintain high levels of integrity in their work. The academic position of a lecturer often reflects their involvement in research, community service, and scientific publications, indicating a broad scope of expertise. This study aims to cluster lecturers based on their academic positions, research activities, community service, and number of publications, using secondary data from the Community Service Research Institute, UPT Academic Positions and Lecturer Certification, and UPT Publications. The clustering was conducted using a non-hierarchical k-means method, which resulted in three clusters: Cluster 1 with 26 members showing minimal productivity in the tridharma tasks, Cluster 2 with 6 members demonstrating high engagement, and Cluster 3 with 20 members with moderate involvement. These findings suggest that universities need to monitor and support lecturers in Cluster 1 to improve their contributions to education, research, and community service. This clustering provides insights that can guide universities in promoting a balanced and active academic environment.
Co-Authors Abdur Rouf, Abdur Hasyim Asyari Qoritunnadyah, Marita