Ridho Vernanda Padantyo, R. M. (2021) ANALISIS PENGGUNAAN METODE PRE-PROCESSING CLAHE PADA KLASIFIKASI COVID 19 MELALUI CITRA RADIOGRAFI MENGGUNAKAN EKSTRAKSI FITUR GLCM DAN KLASIFIKASI SVM. S1 thesis, Universitas Mataram.
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Abstract
Abstract. COVID-19 is a type of disease that transmits a new variant of virus known as Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-COV-2) in the same novel coronavirus family as SARS-CoV and Middle East Respiratory Syndrome Coronovirus (MERS-COV). A fast method to detect the disease is essential to prevent larger transmission and to look after the infected patients. The Chest X-ray, one of the detection methods of COVID-19 can be used in the examination process of suspected cases. In this paper, a COVID-19 detection model through chest x-ray images is proposed by using Grey Level Co-occurrence Matrix (GLCM) with Support Vector Machine (SVM), K-Nearest Neighbor (KNN), and Backpropagation Artificial Neural Network (BP-ANN) classifiers. In this case, Principal Component Analysis (PCA) will be added as a mean to optimize features extraction process. The aim of this work is to find the best classifier for predicting chest x-ray images as normal, pneumonia, or COVID-19 suspect. The BP-ANN emerged as the best classifier with 85,5% accuracy, 85,8% precision, and 86,1% recall.
| Item Type: | Thesis (S1) |
|---|---|
| Keywords (Kata Kunci): | Keywords:. COVID-19, Chest X-ray, Radiographic Image, Grey Level Co-occurrence Matrix, Support Vector Machine, K-Nearest Neighbour, Backpropagation, Neural Network |
| Subjects: | T Technology > T Technology (General) |
| Divisions: | Fakultas Teknik |
| Depositing User: | Rini Trisnawati |
| Date Deposited: | 07 Feb 2022 00:58 |
| Last Modified: | 07 Feb 2022 00:58 |
| URI: | http://eprints.unram.ac.id/id/eprint/27647 |
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