KERNEL: Jurnal Riset Inovasi Bidang Informatika dan Pendidikan Informatika
Vol 2, No 1 (2021)

Diagnosa COVID-19 Chest X-Ray Dengan Convolution Neural Network Arsitektur Resnet-152

Widi Hastomo (Unknown)
Adhitio Bayangkari Satyo Karno (Unknown)



Article Info

Publish Date
25 Aug 2021

Abstract

The availability of medical aids in adequate quantities is very much needed to assist the work of the medical staff in dealing with the very large number of Covid patients. Artificial Intelligence (AI) with the Deep Learning (DL) method, especially the Convolution Neural Network (CNN), is able to diagnose Chest X-ray images generated by the Computer Tomography Scanner (C.T. Scan) against certain diseases (Covid). Resnet Version-152 architecture was used in this study to train a dataset of 10.300 images, consisting of 4 classifications namely covid, normal, lung opacity with 3,000 images each and viral pneumonia 1,000 images. The results of the study with 50 epoch training obtained very good values for the accuracy of training and validation of 95.5% and 91.8%, respectively. The test with 10.300 image dataset obtained 98% accuracy testing, with the precision of each class being Covid (99%), Lung_Opacity (99%), Normal (98%) and Viral pneumonia (98%). 

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Journal Info

Abbrev

kernel

Publisher

Subject

Computer Science & IT Other

Description

1. Teknologi Informasi 2. Rekayasa Perangkat Lunak: a. Rekayasa Kebutuhan b. Pengembangan Game dan Realitas Virtual c. Management Proyek Perangkat Lunak d. User Interface / User Experience 3. Jaringan Komputer: a. Sekuritas Jaringan b. Internet Of Things c. Wireless Network d. Cloud Computing e. ...