Pengembangan Wearable System Berbasis Mobile Untuk Memantau Kondisi Atlet Menggunakan Metode Naïve Bayes
Abstract
This research aims to develop a real-time athlete condition monitoring system through a Flutter-based application utilizing the Naïve Bayes algorithm and Internet of Things (IoT) technology. The system integrates the Max30100 sensor to detect heart rate and SpO? levels, along with the ESP32 module for data communication. The Naïve Bayes algorithm is employed for heart rate data classification, achieving high accuracy in decision-making. Data is transmitted and stored in Firebase, enabling coaches to monitor athletes' physical conditions via graphical visualizations in the application. Testing demonstrates that the Naïve Bayes method achieves 95% accuracy in data classification, and the application successfully displays data in real-time with an intuitive user interface. These results significantly contribute to improving the efficiency and quality of athlete training while providing a reference for further development in IoT-based health monitoring technology.
