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All Journal International Journal of Artificial Intelligence
Shaharudin, Muhammad Hairil
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Computer Science & IT Decision Sciences, Operations Research & Management

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Journal : international journal of artificial intelligence

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Development of a Student Expense Tracking System Using Optical Character Recognition Shaharudin, Muhammad Hairil; Saad, Ahmad Fadli; Yani, Achmad; Manaf, Abdi
International Journal of Artificial Intelligence Vol 12 No 1: June 2025
Publisher : Lamintang Education and Training Centre, in collaboration with the International Association of Educators, Scientists, Technologists, and Engineers (IA-ESTE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36079/lamintang.ijai-01201.741

Abstract

Personal financial literacy is a vital skill for university students, yet many struggle to track their daily expenses due to time constraints and low awareness. This study aims to design and develop a web-based Student Expense Tracking System using Optical Character Recognition (OCR) technology to address this issue. The system allows users to automatically extract and record spending information from receipt images, reducing manual input and improving financial awareness. The development followed the Web Development Life Cycle (WDLC) using the Waterfall model, comprising planning, design, development, and testing phases. Visual Studio Code, Python 3, and Tesseract OCR were employed in system implementation. Wireframes and mockups guided the interface design, while backend development focused on data storage and OCR integration. Functionality testing showed a 100% pass rate across ten scenarios, validating the system's performance in image processing, budget management, and spending visualization. Usability testing using the Post-Study System Usability Questionnaire (PSSUQ) with 30 participants yielded a mean score of 4.45 out of 5, indicating a high level of user satisfaction. The system scored highest on ease of use (4.6), visual design (4.7), and recommendation likelihood (4.8), confirming its intuitive interface and appeal. Slightly lower scores in user confidence (4.1) and data organization (4.2) point to opportunities for interface refinement and improved user guidance. This research concludes that OCR can effectively support financial tracking for students. Future enhancements with NLP and machine learning are recommended to automate expense categorization and improve analytical capabilities.
Student Expense Tracking System Using OCR Saad, Ahmad Fadli; Shaharudin, Muhammad Hairil; Yani, Achmad; Manaf, Abdi; Ismail, Andi Almeira Zocha; Ismail, Andi Regina Acacia
International Journal of Artificial Intelligence Vol 12 No 2: December 2025
Publisher : Lamintang Education and Training Centre, in collaboration with the International Association of Educators, Scientists, Technologists, and Engineers (IA-ESTE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36079/lamintang.ijai-01202.929

Abstract

Nowadays student schedules are packed with their academic and curricular activities. Therefore, Students are no longer tracking their expenses because it is so hard to keep track with their expenses when they a have busy life. The aim of this research is to help students easily track their expenses by automating the process of extracting information from receipts. This research presents a student tracking expenses system using Optical Character Recognition (OCR) technology. The method that was used to develop the system was Website Development Life Cycle (WDLC). The system also uses Image Processing that implements OCR into the system. The system has been tested with a set of sample receipts, and the results show that it is able to accurately extract the relevant information with a high level of efficiency. The initial of this research involved designing the system, which was achieved through the creation of a detailed mockup and wireframe to establish a clear vision for its design. Then, it focused on developing the system, incorporating OCR technology to extract text from receipts. Thorough functional testing ensured that all system features, including user identification, image upload and OCR processing, expenditure management, budget setting, and data visualization, functioned as intended. The system offers users accurate and dependable capabilities for spending pattern analysis, budget management, and expense monitoring. Furthermore, the usability testing was conducted using the Post-Study System Usability Questionnaire (PSSUQ) from 30 students. The mean score of the System Usefulness, Information Quality and Overall Satisfaction is above 4 which indicates that it was appreciated by the students or respondents. Therefore, this system can be a valuable tool for students to manage their finances and make informed decisions about their spending.
Co-Authors Ismail, Andi Almeira Zocha Ismail, Andi Regina Acacia Manaf, Abdi Saad, Ahmad Fadli Yani, Achmad