<![CDATA[Modern technology continues to advance rapidly, impacting various aspects of life, including attendance management systems. One notable innovation is the integration of face recognition and geolocation technology for attendance systems. This technology provides a more efficient and accurate solution for recording attendance compared to conventional methods. Face recognition allows for automatic and quick identity verification, while geolocation ensures that users are in the correct location when marking their attendance. This study aims to design and develop an attendance information system utilizing both face recognition and geolocation technologies. Face recognition is implemented using a TensorFlow model trained to accurately recognize faces. Geolocation data is obtained from the GPS devices on users' smartphones and is used to verify their presence at authorized locations. The system is implemented as an interconnected website and mobile application for storing attendance information. The results of the research and testing indicate that the developed face recognition system can accurately identify faces and distinguish between real and fake faces. Additionally, the geolocation system can effectively verify users' locations and detect the use of spoofed locations. The educators at MA Al Bukhary possess the necessary devices to use this information system, meeting the technology requirements tested. From the user requirements testing, the system received a score of 88,06, categorized as excellent (A).]]>
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