Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi)
Vol 6 No 2 (2022): April 2022

Covid-19 Detection Using Convolutional Neural Networks (CNN) Classification Algorithm

Melly Damara Chaniago (Universitas Muhammadiyah Malang)
Amellia Amanullah Sugiharto (Universitas Muhammadiyah Malang)
Qhistina Dyah Khatulistiwa (Universitas Muhammadiyah Malang)
Zamah Sari (Universitas Muhammadiyah Malang)
Agus Eko (Universitas Muhammadiyah Malang)



Article Info

Publish Date
20 Apr 2022

Abstract

Corona Virus, also known as COVID-19, is one of the new viruses in 2019. Viruses caused by an animal or human diseases are called coronaviruses. Coronavirus will direct respiration in humans. Humans who are exposed to the coronavirus will experience a respiratory infection. The research that will be made helps classify X-rays of the lungs of patients affected by the coronavirus. In this study, the classification of coronaviruses focuses on three classes, namely Covid, Normal, and Viral Pneumonia. This study uses a lung X-ray image dataset. This study has four folders, namely Scenario 1, Scenario 2, Scenario 3, and Scenario 4. This study will use the Convolutional Neural Network (CNN) method by using an architectural model including Convolutional 2D, activation layers, max-pooling layer, dropout layer, flatten, and dense layer. After building the model, the results of accuracy, precision, recall, and f1-score will be obtained in each scenario. The result of the accuracy of Scenario 1 is 97.87%. In Scenario 2, the accuracy is 94.84%, Scenario 3 is 91.66%, and Scenario 4 is 91.41%.

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Journal Info

Abbrev

RESTI

Publisher

Subject

Computer Science & IT Engineering

Description

Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) dimaksudkan sebagai media kajian ilmiah hasil penelitian, pemikiran dan kajian analisis-kritis mengenai penelitian Rekayasa Sistem, Teknik Informatika/Teknologi Informasi, Manajemen Informatika dan Sistem Informasi. Sebagai bagian dari semangat ...