Salat learning is one of the most important processes for every Muslim. The current learning approach requires the teacher or expert to be present in the learning session, which is time and resource-consuming. Previous researchers use both wearable and non-wearable sensors to recognize salat movement. They focus on specific salat movement rather than complete salat movement cycle. This paper present a motion recognition system to enhance salat learning experience. The system helps users recognize the complete salat movements cycle based on salat law by using a multisensor setup for better tracking capability. Three evaluations are conducted to validate the system's performance and its contribution. The first evaluation is to measure success score in recognition accuracy and identify user error. The second evaluation is conducted to compare the proposed system with the traditional-based methodology, and the last evaluation focuses on the user experience and acceptance of the proposed system. The result from performance evaluation shows the system has high accuracy in recognizing salat movement. There is a significant difference in the error rate and success score when comparing the learning methodology. However, users provide positive feedback based on the survey conducted after using the proposed system.
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