Adaptation of Hybrid Filtering in Recommending Degree Course for Diploma Students.

DOI

10.2991/978-94-6463-839-4_58How to use a DOI?

Keywords

Recommendation System; Content Based Filtering; Hybrid program

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.

Copyright

© 2025 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Anis Amilah Shari
AU  - Nurbaity Sabri
AU  - Mohd Rahmat Mohd Noordin
AU  - Ts Dr Khyrina Airin Fariza Abu Samah
AU  - Asma Shazwani Shari
AU  - Wan Muhammad Akmalhadi Wan Mohd Ariffin
PY  - 2025
DA  - 2025/09/16
TI  - Adaptation of Hybrid Filtering in Recommending Degree Course for Diploma Students.
BT  - Proceedings of the 10th Padang International Conference on Education, Economics, Business and Accounting (PICEEBA-2 2022)
PB  - Atlantis Press
SP  - 692
EP  - 701
SN  - 2352-5428
UR  - https://doi.org/10.2991/978-94-6463-839-4_58
DO  - 10.2991/978-94-6463-839-4_58
ID  - Shari2025
ER  -