<![CDATA[In an era where information technology is pervasive, education is impacted significantly. One technology being adopted is face recognition for student attendance authentication, which is more resistant to forgery and manipulation than methods like RFID cards. It offers high accuracy and can function under various conditions, making it effective and efficient. Student attendance is crucial for the effectiveness of the learning process. Traditional methods have limitations in accuracy, speed, and convenience. Institutions have shifted to technology-based methods such as mobile applications or RFID devices, which still require physical interaction. Face recognition, with deep learning, promises to streamline the attendance process by enhancing accuracy and efficiency. Deep learning processes complex data, such as facial images, with high accuracy. Integrating face recognition with deep learning can address challenges like pose variation, facial expressions, and lighting conditions. The objectives of this research aim to make a substantial contribution to the current development of student attendance technology, improving administrative processes in educational institutions.]]>
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