COVID-19 is an epidemic that is currently global. This outbreak was first detected in Wuhan, China in December 2019. Since then this outbreak has claimed hundreds of lives. COVID-19 has similarities to Viral Pneumonia. So it becomes a challenge for researchers to create a method that is able to classify these two diseases. One of the uses of digital image processing is computed tomography (CT-Scan) imaging. Since its introduction in the medical clique in 1972, CT-Scan has grown to be used to image the human lung. The use of this imaging is to find out which part of the lung is affected by the disease. In this study, CT-Scans of normal lungs, COVID-19, and Viral Pneumonia will be classified using the Convolutional Neural Network (CNN). Based on the results of the study, it was found that the proposed method has a training accuracy of 100 percent. While the accuracy of the test is 95 percent.