Covid-19 classification using X-Ray imaging with ensemble learning

T. Siswantining, R. Parlindungan

Research output: Contribution to journalConference articlepeer-review

1 Citation (Scopus)

Abstract

Coronavirus (Covid-19) first appeared in Wuhan, December 2019, and continues to spread rapidly to other countries.one of the countries infected with the Covid-19 virus is Indonesia. In Indonesia, the spread of this virus is very fast. Therefore, we need a detection system to detect people who are infected with this virus or not. Rapid detection of Covid-19 can contribute to control the spread of this disease. Chest x-ray images are one of the first imaging techniques to play an important role in the diagnosis of Covid-19. This research data uses chest x-ray images dataset in the Covid-19 cases. The data used in this study were 170 images data with 130 data for training data and 40 for testing data. In this study, the Neural Network, Support Vector Machine (SVM), and Convolutional Neural Network (CNN) methods were used, then applied to Stacking which is one of the methods of Ensemble Learning. The results of this study indicate that the best accuracy is obtained from the Stacking model with an accuracy of 95%.

Original languageEnglish
Article number012072
JournalJournal of Physics: Conference Series
Volume1722
Issue number1
DOIs
Publication statusPublished - 7 Jan 2021
Event10th International Conference and Workshop on High Dimensional Data Analysis, ICW-HDDA 2020 - Sanur-Bali, Indonesia
Duration: 12 Oct 202015 Oct 2020

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