Implementasi Sistem Pendeteksi Premature Atrial Contraction (PAC) menggunakan Metode Naive Bayes Classifier - Rosyana Lencie Mampioper; Rizal Maulana; Barlian Henryranu Prasetio (Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya, 2022)
Heart disease or cardiovascular disease is one of leading causes of death worldwide. In Indonesia there are more than two million cases per year. Premature Atrial Contraction (PAC) is a heart disease in the atrium section where this heart rhythm disturbance occurs with symptoms of a faster or slower and irregular heartbeat. Currently, Premature Atrial Contraction (PAC) examination is performed by cardiologists with patients undergoing ECG tests. However, the cost of ECG examination is quite expensive and also the pandemic conditions caused restrictions to public places and hospitals. Therefore, a solution is offered in this study to identify early PAC heart rhythm disorders. This study makes a prototype using several devices such as Arduino Nano as Microcontroller, AD8232 Sensor and Electrodes to get ECG signal and also LCD to display the heart information output either â€œnormalâ€ or â€œPACâ€. The main features in this system are RR intervals and QRS complex and apply classification using Naive Bayes Classifier. The results of the naive bayes classification in this study achieved an accuracy value of 91,67% using 24 training data and 12 testing data with an average computation time of 3,35 milisecond.