Enhancing teaching and learning through data-driven optimization of servicing code demand and lecturer allocation using WEKA analysis

The increasing demand for servicing codes across faculties has created a growing need for data-driven decision supports in optimizing lecturer allocation and cost efficiency. This study applies machine learning techniques using the WEKA analytical tool to explore, cluster and classify servicing code...

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Main Authors:	Rochin Demong, Nur Atiqah, Mohamed Razali, Murni Zarina, Kamaruddin, Juliana Noor, Shamsuddin, Sazwan, Awang, Nor Ain, Kamarudin, Norjuliatie, Wan Othman, Noor Faradilla
Format:	Article
Language:	en
Published:	Universiti Teknologi Mara Selangor 2025
Subjects:	History of discoveries, explorations, and travel Teaching (Principles and practice) Electronic Computers. Computer Science
Online Access:	https://ir.uitm.edu.my/id/eprint/129132/1/129132.pdf https://ir.uitm.edu.my/id/eprint/129132/ https://journal.uitm.edu.my/ojs/index.php/Abrij
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