@article{Sumardi_Sudarti_Muldayani_Imron_2022, title={Motorized Driving Safety System Using Eye Detection Analysis Method}, volume={8}, url={https://jppipa.unram.ac.id/index.php/jppipa/article/view/1747}, DOI={10.29303/jppipa.v8i3.1747}, abstractNote={<p>Traffic accident, particularly two-wheeled vehicles, is a problem for the Government, especially the Resort Police Traffic Unit (<em>Satlantas Polres</em>). The factor that causes the traffic accident incident is divided into three types, namely human factor, vehicle factor, and road or environment factor. The human factor is the most common factor for an accident. Fatigue factor that causes someone to feel sleepy while driving often results in a traffic accident. Based on the problem, the researcher wanted to create a technology innovation of a motorized driving safety system in the form of a helmet. The researcher made an innovation of a helmet that can detect drowsiness through the driver’s eye blink duration. The drowsiness will be detected by using a camera sensor. The camera sensor used was Open MV camera. The method used in detecting sleepy drivers was the eye detection analysis method. The method enable detection based on the data of the duration of eye condition when it is closed and open. The closed eye has a low RBG mean value of 110-113 and an RBG median value of 99-109. Whereas opened eye has a higher RGB mean value of 179-206 and RGB median value of 178-206. The result of the research showed that someone’s sleepy condition occurred when closing their eyes for more than 0.4 seconds to 4 seconds. The helmet is also equipped with GPS to monitor the position in the event of an accident as an emergency response effort.</p>}, number={3}, journal={Jurnal Penelitian Pendidikan IPA}, author={Sumardi, Sumardi and Sudarti, Sudarti and Muldayani, Wahyu and Imron, Arizal Mujibtamala Nanda}, year={2022}, month={Jul.}, pages={1575–1580} }