| dc.description.abstract | This research aims to develop a bike fitting system based on digital image processing for road bikes. The method used in this research involves the utilization of the OpenCV and Mediapipe libraries in the Python programming language to detect the rider's body pose from a video stream captured using a webcam. The obtained body pose data is then used to calculate important angles such as the elbow angle, hip angle, knee angle, and ankle range, which are related to the correct riding position for road bikes. In this study, a comparison is made between the resulting body angles and the desired angle ranges considered as the ideal position for bike fitting on road bikes. If the body angles fall within the desired range, the system labels it as "Sudah Fit," while if the body angles deviate from the desired range, the system labels it as "Belum Fit." The research findings demonstrate that the bike fitting system based on digital image processing using a webcam can provide useful visual feedback to improve the rider's body position on a road bike. By observing the generated body angles and the "Sudah Fit" or "Belum Fit" label, cyclists can adjust their positions to align with the ideal position in bike fitting. Therefore, this system can help enhance the comfort and performance of road bike riders. | en_US |
