Enhancing Financial Literacy: A Progressive Web Application Approach for Malaysian Youth

Financial management is a crucial skill that individuals of all age ranges should acquire and master. It offers a transparent view of our financial status, enabling us to comprehend where our expenses are directed and manage every facet of our finances. Studies have indicated that Malaysian youth la...

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Bibliographic Details
Main Authors: Jun-Xuan Kok, Sin-Ban Ho, Chuie-Hong Tan
Format: Article
Language:English
Published: MMU Press 2025-02-01
Series:Journal of Informatics and Web Engineering
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Online Access:https://journals.mmupress.com/index.php/jiwe/article/view/1312
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Summary:Financial management is a crucial skill that individuals of all age ranges should acquire and master. It offers a transparent view of our financial status, enabling us to comprehend where our expenses are directed and manage every facet of our finances. Studies have indicated that Malaysian youth lack understanding in financial management. Nowadays, with so many people using the internet, we have the opportunity to share this expertise with a larger audience. Providing easily accessible materials for learning about and managing personal finances is essential to comprehending people's individual financial circumstances. In light of this, the purpose of this article is to develop a useful, progressive web system for personal finance management that makes budgeting and cost tracking easier. This personal finance management system will be implemented using the Tailwind Cascading Style Sheets, Firebase, and React framework as development tools. React frameworks are used due to their ability to produce dynamic user interfaces. To sum up, this user-friendly interface mechanism enables the formulation of budgets and the tracking of expenses. It also consists of other features for data visualization, such as charts. This research has the potential to add some additional enhancements to its existing functionality. For instance, it could introduce a predictive budgeting function that uses historical user spending data to perform predictive analysis.
ISSN:2821-370X