Azral Satrani
Program Studi Ilmu Komputer, Universitas Bumigora, Indonesia

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Implementation Anti-Fraud Security on Smart Campus Attendance System Using Face Recognition Liveness Detection and Anti-Fake GPS Geofencing Azral Satrani; Tanwir Tanwir; Dading Oktaviadi Resminanta; Muhammad Maulana; Kartarina Augustin; Gede Yogi Pratama
Jurnal Teknologi Informasi dan Multimedia Vol. 8 No. 3 (2026): August
Publisher : Sekawan Institut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35746/jtim.v8i3.1057

Abstract

In the digital era, the fingerprint-based attendance system used by University of Bumigora where considered ineffective and inefficient due to hygiene issues, physical vulnerability, the risk of for-gery, and slow processing speed during peak hours. In addition, as the digital attendance system develops, new challenges arise in the form of biometric data manipulation through presentation attacks (photos/videos/masks) and location manipulation using fake GPS applications. This dual vulnerability is a critical issue that can damage data integrity and the governance of educational institutions. To address these issues, this study proposes the design and development of a Smart Campus attendance system that integrates two anti-fraud security mechanisms, namely Face Recognition liveness  detection and Anti-Fake GPS Geofencing. Liveness Detection technology functions to detect real-life signs to distinguish real faces from fake representations, while An-ti-Fake GPS validates the signal consistency and physicality of users within a predetermined campus geographic radius (geofence). This system was developed using Agile methods to ensure adaptive and structured development. From a technological perspective, this system integrates the Vue JS framework in the user interface (UI) due to its robust performance, and the Laravel frame-work in the backend due to its advantages in Model-View-Controller (MVC) architecture, security, and high scalability. Through this approach, the study aims to evaluate the effectiveness of a lay-ered anti-fraud mechanism in preventing fraud and measure improvements in administrative effi-ciency compared to conventional fingerprint systems.