School teacher-subject allocation management system
The timetable systems for allocating teachers to subjects have improved from only digitalizing the management of timetable data to fully automating the timetabling process. However, the timetabling solutions available in the market are still having some shortcomings, leading to various issues that...
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Format: | Final Year Project / Dissertation / Thesis |
Published: |
2024
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Online Access: | http://eprints.utar.edu.my/6557/1/SE_2003334_FYP_Report_%2D_DennisYapJianYuan_DENNIS_YAP_JIAN_YUAN.pdf http://eprints.utar.edu.my/6557/ |
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Institution: | Universiti Tunku Abdul Rahman |
Summary: | The timetable systems for allocating teachers to subjects have improved from only digitalizing the management of timetable data to fully automating the timetabling process.
However, the timetabling solutions available in the market are still having some shortcomings, leading to various issues that require solutions. So, the primary objective of this project is to identify the existing problems in the similarly School Teacher Subject Allocation Management
Systems (STSAMS) used in public schools. Then, the project aims to propose optimal solutions to enhance these systems, solving any weaknesses or issues they may currently face. This project will build STSAMS as a web-based application in React.js that is equipped with API server, database, and the allotment algorithm with the Scrum methodology. The algorithm that will be used is Genetic Algorithm which has NP level of difficulty. So, requirement gathering using multiple methods like interviews and system analysis will be performed the narrow down the constraints used in the algorithm, while also lowering the complexity of the Genetic
Algorithm to reduce the time complexity. Not just that, Genetic Algorithm, a meta-heuristic is also used to solve the clashing problem faced by existing system using deterministic algorithm. The STSAMS in this project is evaluated by using user acceptance test and unit test. The UAT results showed that STSAMS reached 75% user satisfaction level when the users are using the application.
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