• Erzha Anges Farhandy (1*) Universitas Mercu Buana
  • Sukma Wardhana (2) Universitas Mercu Buana

  • (*) Corresponding Author
Keywords: Classification, Covid-19, CNN, deep learning, Chest X-Ray


CoV-2 virus this disease is spreading rapidly throughout the world. Various studies were carried out to control the spread of Covid-19. One way to detect Covid-19 is to study chest X-ray images of patients with Covid-19 symptoms. However, to detect Covid-19 through x-ray images, there are currently few radiology specialists needed. This study researched to detection of Covid-19 disease through chest x-ray images with a deep learning approach based on a convolutional neural network (CNN). Before training the model, data preprocessing is carried out, such as labeling and resizing. This study uses a CNN model with three layers of convolution and max-pooling layers and a fully-connected layer for the output. The results of the training using the CNN method produced a pretty good performance, with the best training accuracy (acc) value obtained in the 31st epoch with a value of 0.9593, training loss (loss) 0.1306, validation accuracy (val_acc) 0.9604, and loss validation (val_loss). 0.1399.


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How to Cite
Farhandy, E., & Wardhana, S. (2022). CLASSIFICATION OF CORONAVIRUS DISEASE (COVID-19) THROUGH CHEST X-RAY IMAGES BASED ON DEEP LEARNING. Jurnal Pilar Nusa Mandiri, 18(2), 145-152.
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