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All Journal Journal of Digital Technology and Computer Science
Aslina Gulo
Institut Teknologi Sawit Indonesia, Medan, Indonesia
Computer Science & IT Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Engineering

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Design and Development of a Web-Based Attendance System Using QR Code ID Cards and Geofencing Validation Aslina Gulo; Ritna Wahyuni; Ratu Mutiara Siregar
Journal of Digital Technology and Computer Science Vol. 3 No. 2 (2026): April 2026
Publisher : Academic Bright Collaboration

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.66053/dtcs.v3i2.901

Abstract

Purpose – Manual attendance in plantation operations suffers from high administrative vulnerability and data fraud, creating an efficiency gap for remote work units. This study aims to develop a low-cost, web-based employee attendance information system utilizing static QR Code ID cards for Palm Oil Plant. Methods – The system was engineered using a plan-driven Waterfall lifecycle model, encompassing UML design, Laravel 10 framework implementation, a MySQL database layer, and rigorous verification via 22 granular Black Box Testing operational scenarios. Findings – The prototype successfully deployed multi-layered authentication features, returning a 100% "Compliant" status during testing. Single-user performance benchmarks recorded highly responsive empirical latencies: 320 ms for QR matrix string extraction, 145 ms for geofence processing, and 42 ms for MySQL database commits. Research Implications – The study's scope was limited by single-user benchmark testing and a lack of live database API integration into corporate SAP payroll systems. Practically, this architecture supports the technical feasibility of open-source web applications in shifting infrastructure weights away from enterprises operating in severe industrial dust environments. Originality – The value lies in the operational synthesis of an open-source framework, Haversine-driven geofencing, and visual capture customized for low-connectivity plantation workers. Future steps must focus on transitioning toward offline-first Progressive Web Apps (PWAs) and integrating lightweight machine learning models (such as FaceNet or MediaPipe) to transition from passive visual documentation to automated biometric verification.
Co-Authors Ratu Mutiara Siregar Ritna Wahyuni