Abstract
Heart rate and body temperature are essential factors that must be considered before exercise is essential to optimize exercise and know the body's condition. The trainer conducts a health check, and management evaluates the exercise results conducted on the athlete. The Internet of Things is the solution provided to facilitate the monitoring of health conditions and measure exercise intensity. Before and after exercise, the health condition monitoring system is designed to determine the user's health condition by measuring heart rate and body temperature as parameters for decision-making by applying the Naïve Bayes method. The Naive Bayes method is rule-based with the python sci-kit-learn programming language and data communication with MQTT. From the study results, the Sports Health condition monitoring system has succeeded in providing monitoring results, condition prediction decisions, and the accuracy of the Naïve Bayes method by 75%.