<![CDATA[Personal Information Management (PIM) at the University of Nahdlatul Ulama Surabaya (UNUSA) continues to face challenges, particularly in managing attendance within the eSorogan system and the UNUSA Academic Information System (SIM). This study proposes and implements a face recognition-based PIM system designed to automate the identification and recording of members of the UNUSA academic community. The system integrates AI-powered cameras with a web-based dashboard, referred to as the Lobby PIM Dashboard, which displays real-time information related to recognized individuals. The workflow begins with image capture and face detection by the AI camera, followed by data transmission to the server via an API for identification and information retrieval. The system generates detection logs and attendance records, which are stored and presented through the dashboard interface. The results demonstrate that the proposed system can support more efficient attendance management and provide accessible academic information for lecturers and students. Overall, this implementation contributes to improving administrative processes and enhancing the effectiveness of academic services at UNUSA.]]>
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