Implementasi Sistem Pendeteksi Premature Ventricular Contraction (PVC) Aritmia Menggunakan Metode Naive Bayes - Gusti Arief Gilang; Rizal Maulana; Wijaya Kurniawan (Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya, 2018)
Premature Ventricular Contraction (PVC) Arrhythmia is an anomaly heartbeat that occurs because of the heartbeat rhythm disorder in the ventricles. PVC that happens too often can lead to dangerous disease such as heart failure.From this problem, it is necessary to make a system that detect the type of PVC that can be used independently so it can reduce the number of individuals who have a heart disease because of PVC. This research has a parameter used to make a comparison on each type of PVC, that is heartbeat time interval and BPM by using ECG technique to measure the heartbeat. Determination of PVC type with those parameters is obtained from ECG AD8232 sensor value by Arduino Uno using Naive Bayes method. Naive Bayes is used in this research because PVC can be classified by using nine features as the basis, that is eight R Interval value and BPM value. This research outputs is displayed using Processing. A BPM tests of this research gives 8,558% percentage average error. Furthermore, a classification result test using Naive Bayes with 46 training data and 14 test data gives 92,857% accuration with 7,2 second average computation time.