This research aims to design and develop a Smart Keyless Locker using Face Recognition technology based on the Internet of Things (IoT) to enhance security and efficiency in locker usage within classroom environments at Jakarta Global University. The developed system consists of a camera module for facial recognition, a microcontroller as the control unit, a solenoid lock as the locking mechanism, and an IoT platform for real-time data management. The research method includes hardware and software scenarios design, system integration, and performance testing under several usage. The Face Recognition algorithm was implemented using the OpenCV library with the Haar Cascade Classifier model, while data communication between devices was conducted via a serial USB connection. Testing results indicate that the system can recognize faces with an accuracy rate of 89.39% and an average response time of 4.75 seconds from detection to unlocking. This implementation offers keyless access convenience, reduces the risk of key loss or duplication, and enables remote monitoring by administrators. Based on the results, the IoT-based Smart Keyless Locker with Face Recognitionis deemed suitable as a secure, efficient, and modern locker management solutionin campusen vironments.
Keywords: Face Recognition, Internet of Things, Smart Locker, OpenCV, Serial
USB.