Smart student timetable planner

Timetable planning is a crucial yet challenging task for university students, as traditional manual methods are often time-consuming, prone to errors, and lack collaborative support. Students frequently face difficulties in avoiding timetable clashes, managing personal preferences, and coordinating...

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Bibliographic Details
Main Author: Wong, Xin Tong
Format: Final Year Project / Dissertation / Thesis
Published: 2025
Subjects:
Online Access:http://eprints.utar.edu.my/7245/1/fyp_CS_2025_WXT.pdf
http://eprints.utar.edu.my/7245/
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Summary:Timetable planning is a crucial yet challenging task for university students, as traditional manual methods are often time-consuming, prone to errors, and lack collaborative support. Students frequently face difficulties in avoiding timetable clashes, managing personal preferences, and coordinating with peers, which can lead to inefficiencies and added stress. To address these issues, this project introduces the Smart Student Timetable Planner, a system developed to streamline academic scheduling by providing both automated and manual timetable management options. The objectives of this project are to generate conflict-free and customizable schedules, enable real-time collaboration among students, and offer administrative tools for maintaining course information. The project scope encompasses features such as secure login, course selection with conflict detection, timetable history, comparison between auto-generated and manual schedules, collaboration modules, and export functionality. To achieve these objectives, the system adopts the Rapid Application Development (RAD) methodology, ensuring iterative design, prototyping, and user feedback integration throughout the process. The system is implemented using Node.js with Express for server-side development, HTML, CSS, and JavaScript for the frontend, and Socket.IO for real-time collaboration. Course data is managed in CSV format, parsed into JSON for fast processing, while sessionStorage and localStorage handle user data within active sessions. A Genetic Algorithm forms the core scheduling engine, generating optimized timetables that respect both hard constraints, such as avoiding clashes, and soft constraints, such as personal preferences.The final output of this project is a functional web-based timetable planner that successfully enhances scheduling efficiency, reduces the likelihood of errors, and improves the overall academic planning experience. With its flexible design, collaborative features, and administrative integration, the Smart Student Timetable Planner demonstrates significant potential as a scalable solution for modern university scheduling needs.