Efficient Scaling of Convolutional Neural Network for Detecting and Classifying Pneumonia Disease

Abstract

Lung is one of vital human organ. When lung is suffered by any cause, it will impact on the body's metabolic processes. One of disorder in the lung is pneumonia. Pneumonia is caused by pathogenic microorganisms, namely bacteria, viruses, and fungi. In this study, pneumonia diseases are classified using deep learning method, which is EfficientNet Architecture Convolutional Neural Network. This study is using secondary data which 2430 data were used. About 486 data were used for testing process and 1944 data used for training process. By using this method, it can be concluded that the system designed is able to classify 3 types of x-ray images. The results obtained in this study are 89.09% accuracy and 1.8934 loss. For other parameters such as f-1 score, recall and precision, the average value for each are 0.87;0.91 and 0.89.