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Abstract

Data from WHO 2015 shows that 70% of deaths in the world are caused by non-infection diseases, 45% are caused by heart and blood vessel disease, namely 17.7 million from 39.5 million deaths.  Riset Kesehatan Dasar (Riskesdas) reported that in 2018, there were 15 of 1000 people, or 2,784,064 individuals in Indonesia suffering from heart disease. Symptoms of heart abnormalities often come suddenly. Therefore, early recognition can help to avoid heart attacks. Doctors currently use a heart sound / phonocardiogram (PCG) to assess the performance of the heart using a stethoscope. The PCG’s diagnosis is very influenced by the subjectivity of doctors because of its relatively weak and physical limitations. So that the possibility of a False Positive Result happening is quite high. To minimize this risk, a Computer Aided Diagnosis (CAD) PCG signal was developed. Several studies have proposed a PCG diagnostic method using the wavelet or Welch method and based on Neural Network are more complex. In this study, a simple diagnosis method is proposed so that the computation is easier and faster with good accuracy. The PCG signal is amplified twice, then the Fast Fourier Transform (FFT) process is carried out to obtain the characteristics of the fundamental frequency and max amplitude. The classification stage uses the Multi Layer Perceptron (MLP). From testing of 55 data PCG, the results obtained accuracy of 90%, sensitivity of 80%, PPV of 100% and NPV of 83.33%.
Keywords: PCG, CAD, FFT, frekuensi fundamental, classification

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