Adaptation of Hybrid Filtering in Recommending Degree Course for Diploma Students

Anis Amilah Shari (), Nurbaity Sabri, Mohd Rahmat Mohd Noordin, Ts Dr Khyrina Airin Fariza Abu Samah, Asma Shazwani Shari and Wan Muhammad Akmalhadi Wan Mohd Ariffin
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Anis Amilah Shari: Universiti Teknologi MARA, College of Computing, Informatics and Mathematics
Nurbaity Sabri: Universiti Teknologi MARA, College of Computing, Informatics and Mathematics
Mohd Rahmat Mohd Noordin: Universiti Teknologi MARA, College of Computing, Informatics and Mathematics
Ts Dr Khyrina Airin Fariza Abu Samah: Universiti Teknologi MARA, College of Computing, Informatics and Mathematics
Asma Shazwani Shari: Universiti Teknologi MARA Campus Machang, Faculty of Business and Management
Wan Muhammad Akmalhadi Wan Mohd Ariffin: Universiti Teknologi MARA, College of Computing, Informatics and Mathematics

A chapter in Proceedings of the 10th Padang International Conference on Education, Economics, Business and Accounting (PICEEBA-10 2022), 2025, pp 692-701 from Springer

Abstract: Abstract Education is a crucial aspect of human evolution; decades of technical progress can be attributed to the advancement and collection of information. More education years are expected to increase production and thus income by offering information, skills, and a problem-solving mindset. Thus, having higher education would present a better work opportunity. Every year, the number of dropouts has increased significantly, one of the factors being students struggle to choose a program that is suitable for them. The effects can be seen in depressive symptoms in students due to the stress of education. This project is developed to provide a method of recommending degree program for diploma students to help overcome the problem. Students can make more informed judgements and boost their chances of academic achievement by providing a recommendation system based on program details. The project implements content-based filtering to produce recommendations based on the program that is offered in the Faculty of Computer and Mathematical Sciences. Modified waterfall methodology is used as the Software Development Life Cycle methodology to make sure that the system is completed and achieves the objectives that were set. The system uses the program details for five programs as the item for the content-based filtering algorithm. The input for the system is taken from the user’s input from answering a set of questionnaires. Functionality testing showed that the system can produce a baseline recommendation for the user, with the recommended programs ranked in order of the highest to lowest likelihood probability.

Keywords: Recommendation System; Content Based Filtering; Hybrid program (search for similar items in EconPapers)
Date: 2025
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DOI: 10.2991/978-94-6463-839-4_58

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