Implementasi Algoritma SVM (Support Vector Machine) Dalam Klasifikasi Penyakit Paru-Paru Berdasarkan Fitur Pola Bentuk

Abstract

There are many implementations of classification data mining algorithms in a case, and for this study the Support Vector Machine algorithm was used to classify lung images based on normal and pneumonia categories. The lung image used was obtained from the kaggle site. Lungs are organs of respiration (breathing) associated with the respiratory system and circulation (blood circulation) in the body of vertebrates that breathe air. In order for the identification of lung disease to be optimal, it will be more effective and efficient to create an application system for classifying lung diseases. This application system is built using the method Support Vector Machine (SVM). The method is Support Vector Machine used to classify diseases in the lungs and the variables used in this algorithm are taken from the extraction of shape features, including the Metric and Eccentricity values. This application system is built using the Matlab IDE. Matlab is a environment computing numerical and language programming fourth generation computer. The method used is data collection and system design. The result of this application system is a classification between normal lungs and diseased lungs, based on the results of calculations grayscale on x-ray images.