International Journal For Multidisciplinary Research

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iTrack QR: An Intelligent Faculty Attendance Monitoring System with QR Code and Business Intelligence Integration for the University of Perpetual Help System Manila

Author(s) Mr. John Chris Capulong Barabad, Mr. Emmanuel Elpidio Sta Maria Mariscotes, Mr. Rodel Martin Tungol, Ms. Anna Liza Ognita Villanueva
Country Philippines
Abstract This study developed and evaluated iTrack QR: An Intelligent Faculty Attendance Monitoring System with QR Code and Business Intelligence Integration for the University of Perpetual Help System Manila. The system was designed to address the limitations of traditional attendance monitoring methods, which are often inefficient, error-prone, and lack real-time data processing and analytical capabilities. Specifically, the study aimed to improve attendance accuracy, enhance security through multi-layer validation, and support data-driven decision-making using Business Intelligence tools.

A descriptive-developmental research design was employed to guide the design, development, implementation, and evaluation of the system. The system integrates QR code scanning, device UID validation, and selfie-based identity verification to ensure secure and accurate attendance recording. It also includes Business Intelligence dashboards for generating reports and analyzing attendance trends. The system was evaluated using ISO/IEC 25010:2023 software quality standards. Data were collected from IT experts and faculty members through structured survey questionnaires using a Likert scale, and results were analyzed using weighted mean.

Findings revealed that iTrack QR achieved high levels of effectiveness in terms of functionality, performance efficiency, reliability, usability, and security, as evaluated by IT experts. Faculty members also demonstrated strong acceptance of the system, confirming that it is practical, user-friendly, and efficient in real-world use. The integration of QR technology with multi-layer validation mechanisms significantly reduced the risk of proxy attendance, while the Business Intelligence component enabled meaningful interpretation of attendance data.

The study concludes that iTrack QR is a reliable, secure, and effective solution for modernizing faculty attendance monitoring systems. It contributes to improving operational efficiency, ensuring data accuracy, and supporting evidence-based decision-making in higher education institutions. Future enhancements may focus on improving system scalability, cross-platform compatibility, and advanced analytics to further strengthen its institutional impact.
Keywords QR Code Attendance, Faculty Attendance Monitoring, Business Intelligence, Device UID Verification, Selfie Verification, Data-Driven Decision Making, Higher Education Systems, iTrack QR
Field Computer > Artificial Intelligence / Simulation / Virtual Reality
Published In Volume 8, Issue 2, March-April 2026
Published On 2026-04-12
DOI https://doi.org/10.36948/ijfmr.2026.v08i02.74124
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