Rancang Bangun Sistem Pendeteksi Kantuk Untuk Keamanan Berkendara Berbasis Website - Ahmad Zikri (Jurnal Sains Informatika Terapan, 2025)
Traffic accidents are often caused by drowsy drivers, which significantly reduce concentration, alertness, and reaction time while driving. This study aims to design and develop a web-based drowsiness detection system using a camera as the primary visual sensor. The system integrates digital image processing and artificial intelligence techniques to analyze the driver’s eye and mouth movements in real time with a high level of accuracy. When early signs of drowsiness are detected, the system provides an instant alert through a web-based interface that can be accessed both locally and remotely. Experimental results show that the system can detect drowsiness with 92% accuracy, an average response time of 1.2 seconds, and stable performance under various lighting and environmental conditions. The implementation of this system proves to be effective, reliable, and low-cost in preventing accidents caused by fatigue. Therefore, this innovative technology offers a practical, efficient, scalable, and affordable solution to enhance road safety and driver awareness for both private and commercial vehicles.