The Comparison of SVM and ANN Classifier for COVID-19 Prediction

Coronavirus 2 (SARS-CoV-2) is the cause of an acute respiratory infectious disease that can cause death, popularly known as Covid-19. Several methods have been used to detect COVID-19-positive patients, such as rapid antigen and PCR. Another method as an alternative to confirming a positive patient...

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Main Authors: Ditha Nurcahya Avianty, Prof. I Gede Pasek Suta Wijaya, Fitri Bimantoro
Format: Article
Language:English
Published: Udayana University, Institute for Research and Community Services 2022-08-01
Series:Lontar Komputer
Online Access:https://ojs.unud.ac.id/index.php/lontar/article/view/79732
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author Ditha Nurcahya Avianty
Prof. I Gede Pasek Suta Wijaya
Fitri Bimantoro
author_facet Ditha Nurcahya Avianty
Prof. I Gede Pasek Suta Wijaya
Fitri Bimantoro
author_sort Ditha Nurcahya Avianty
collection DOAJ
description Coronavirus 2 (SARS-CoV-2) is the cause of an acute respiratory infectious disease that can cause death, popularly known as Covid-19. Several methods have been used to detect COVID-19-positive patients, such as rapid antigen and PCR. Another method as an alternative to confirming a positive patient for COVID-19 is through a lung examination using a chest X-ray image. Our previous research used the ANN method to distinguish COVID-19 suspect, pneumonia, or expected by using a Haar filter on Discrete Wavelet Transform (DWT) combined with seven Hu Moment Invariants. This work adopted the ANN method's feature sets for the Support Vector Machine (SVM), which aim to find the best SVM model appropriate for DWT and Hu moment-based features. Both approaches demonstrate promising results, but the SVM approach has slightly better results. The SVM's performances improve accuracy to 87.84% compared to the ANN approach with 86% accuracy.
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spelling doaj.art-6900c75d8e1845988046ad4e64c193782022-12-22T02:38:32ZengUdayana University, Institute for Research and Community ServicesLontar Komputer2088-15412541-58322022-08-0113212813610.24843/LKJITI.2022.v13.i02.p0679732The Comparison of SVM and ANN Classifier for COVID-19 PredictionDitha Nurcahya AviantyProf. I Gede Pasek Suta WijayaFitri BimantoroCoronavirus 2 (SARS-CoV-2) is the cause of an acute respiratory infectious disease that can cause death, popularly known as Covid-19. Several methods have been used to detect COVID-19-positive patients, such as rapid antigen and PCR. Another method as an alternative to confirming a positive patient for COVID-19 is through a lung examination using a chest X-ray image. Our previous research used the ANN method to distinguish COVID-19 suspect, pneumonia, or expected by using a Haar filter on Discrete Wavelet Transform (DWT) combined with seven Hu Moment Invariants. This work adopted the ANN method's feature sets for the Support Vector Machine (SVM), which aim to find the best SVM model appropriate for DWT and Hu moment-based features. Both approaches demonstrate promising results, but the SVM approach has slightly better results. The SVM's performances improve accuracy to 87.84% compared to the ANN approach with 86% accuracy.https://ojs.unud.ac.id/index.php/lontar/article/view/79732
spellingShingle Ditha Nurcahya Avianty
Prof. I Gede Pasek Suta Wijaya
Fitri Bimantoro
The Comparison of SVM and ANN Classifier for COVID-19 Prediction
Lontar Komputer
title The Comparison of SVM and ANN Classifier for COVID-19 Prediction
title_full The Comparison of SVM and ANN Classifier for COVID-19 Prediction
title_fullStr The Comparison of SVM and ANN Classifier for COVID-19 Prediction
title_full_unstemmed The Comparison of SVM and ANN Classifier for COVID-19 Prediction
title_short The Comparison of SVM and ANN Classifier for COVID-19 Prediction
title_sort comparison of svm and ann classifier for covid 19 prediction
url https://ojs.unud.ac.id/index.php/lontar/article/view/79732
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