Klasifikasi Penyakit Paru-Paru Berdasarkan Suara Paru-Paru Menggunakan Metode MFCC dan SVM

Abstract

The lungs are vital organs that function as a place for oxygen exchange. The lungs are one of the organs that have an important role for humans to survive. The importance of maintaining lung health to avoid dangerous diseases. If the health of the lungs is not taken care of properly, it will make the lungs unable to function normally and can cause disturbances in the respiratory system. The types of lung diseases that are suffered by many people in the world such as cough, asthma, bronchitis, tuberculosis, and so on. Therefore, this study will classify lung diseases based on lung sounds using the MFCC method which will be used at the feature extraction stage and the SVM method used at the data classification stage. The testing phase used is K-Fold Cross Validation and also Confusion Matrix to determine the amount of data that is identified correctly and to determine the level of accuracy generated. After going through several processes to classify the lungs based on the sound of the lungs, the accuracy rate is quite good, which is 80%.