Implementasi Sistem Pendeteksi Obstructive Sleep Apnea berdasarkan Parameter Interval QT dan Interval PR menggunakan Metode Naive Bayes - Iqbal Koza; Rizal Maulana; Hurriyatul Fitriyah (Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer, 2021)
Obstructive Sleep Apnea is a condition in which breathing stops momentarily during sleep and repeats several times. If this disorder is not treated further, it can cause complications in the form of lack of sleep, fatigue and eye problems. For now, sleep apnea examination can only be checked in a hospital and is expensive. Therefore, in this study a system for detecting obstructive sleep apnea was created which did not require too much money. The tools to be used are the Arduino Uno microcontroller as a place for the system program, the ECG AD8232 sensor to detect electrical activity in the heart which is attached to the chest using 3 electrodes, and a 16x2 LCD to display the final result. This study uses the Naive Bayes classification in classifying the electrical activity of the heart. The features in the classification of the naive Bayes method are the QT Interval and the PR Interval, the results of which will be displayed on the LCD in the form of "Normal" or "Sleep Apnea". There were 24 test data taken and 48 training data used in the Naive Bayes classification test. The results of the accuracy test using Naive Bayes were 87.5%. And the results of computational time testing were carried out 24 times with an average value of 1,044.2083 ms.