KLASIFIKASI PENYAKIT COVID-19 MELALUI HASIL CITRA X-RAY MENGGUNAKAN METODE CNN

NAMIRA, MAHASTI and Suprapto, Bhakti Yudho (2023) KLASIFIKASI PENYAKIT COVID-19 MELALUI HASIL CITRA X-RAY MENGGUNAKAN METODE CNN. Undergraduate thesis, Sriwijaya University.

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Abstract

Covid-19 is a disease caused by a corona virus. The test to detect COVID-19 is PCR (Real-time polymerase chain reaction) and radiological images such as CT-Scan and X-Ray also have an important role in detecting COVID-19 patients at an early stage. Many researchers in the IT field observe that X-Ray images can be utilized and developed to help detect COVID-19 in patients. One of the methods used in radiological image classification is the Convolutional Neural Network (CNN). This study aims to obtain performance results from CNN for detecting COVID-19 and Normal disease in X-Ray images with datasets originating from hospitals in Indonesia using 4 architectures, namely ResNet50, MobileNet, VGG19, and Modification Model. The training results show that the model with the MobileNet architecture provides the best performance with an accuracy of 95.31% after going through 500 epochs. The time for the process is 7 hours 30 minutes. This model is then used to test 400 data with a success rate of 81%. This model was then tested on medical personnel with new data and the results obtained were 70% or able to detect 7 out of 10 new X-ray image data. The use of the Convolutional Neural Network (CNN) method has proven effective in detecting COVID-19 through chest X-Ray images.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	X-Ray, Covid-19, CNN (Convolutional Neural Network.)
Subjects:	T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK1-9971 Electrical engineering. Electronics. Nuclear engineering > TK1 Electrical engineering--Periodicals. Automatic control--Periodicals. Computer science--Periodicals. Information technology--Periodicals. Automatic control. Computer science. Electrical engineering. Information technology.
Divisions:	03-Faculty of Engineering > 20201-Electrical Engineering (S1)
Depositing User:	Mahasti Namira
Date Deposited:	12 Jul 2023 06:43
Last Modified:	12 Jul 2023 06:43
URI:	http://repository.unsri.ac.id/id/eprint/116070

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