<![CDATA[The increasing number of motorcycles owned by students at Universitas Andalas has led to inefficiencies in the manual parking card system, including frequent card loss and reduced operational effectiveness. To address this issue, a motorcycle access control system is designed using QR codes integrated with Optical Character Recognition (OCR). The system utilizes a Raspberry Pi 4 Model B, Logitech C270 HD webcam, and a barcode scanner to capture motorcycle license plate images, process them with Convolutional Neural Network (CNN) and Tesseract OCR to extract plate text, and generate a unique QR code for each vehicle. The QR code is used for both entry and exit validation, replacing the need for manual parking cards. Data is stored and managed in a MySQL database, enabling quick retrieval and verification. System testing showed high accuracy in license plate detection and QR validation, ensuring security, efficiency, and ease of use while reducing operational costs. This solution offers a scalable approach for campus, residential, and office access control systems.]]>
