Pengembangan Wearable System Berbasis Mobile Untuk Memantau Kondisi Atlet Menggunakan Metode Naïve Bayes - Dewi, Ni Wayan Sani Utari; Pramartha, Cokorda Rai Adi; Rahayuda, I Gede Surya; Eka Karyawati, Anak Agung Istri Ngurah (JELIKU (Jurnal Elektronik Ilmu Komputer Udayana), 2025)
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.