DIAGNOSIS OF CORONAVIRUS DISEASE 2019 (COVID-19) SURVEILLANCE USING C4.5 ALGORITHM

Diagnosis Penyakit Coronavirus 2019 (COVID-19) Surveillance Menggunakan Algoritma C4.5

DOI: https://doi.org/10.33480/pilar.v16i1.1293
Keywords: Artificial Intelligence, Coronavirus Disease 2019, COVID-19 Diagnosis, Decision Tree, C4.5 Algorithm

Abstract

Coronavirus Disease 2019 (COVID-19) has become a pandemic in Indonesia as a non-natural disaster in the form of disease outbreaks which must be undertaken as a response. The Ministry of Health in the Republic of Indonesia published a guidebook for prevention and control of COVID-19 in its response efforts. This guideline is intended for health officials as a reference in preparing for COVID-19. This handbook contains early detection and response activities to identify conditions of PDP, ODP, OTG, or confirmed cases of COVID-19. The efforts made are adjusted to the world situation progress from COVID-19 which is monitored by the World Health Organization (WHO). From the results of documentation studies that have been carried out on the COVID-19 pandemic in Indonesia, there are several problems that must be resolved from the prevention of the disease outbreak COVID-19. Lack of knowledge and awareness of the general public in the prevention and control of COVID-19 is one of the factors increasing the spread of that virus in Indonesia. Furthermore, there are difficulties in carrying out surveillance, early detection, contact tracing, infection prevention or control, and risk communication or people empowerment. This is due to the lack of implementation and testing on artificial intelligence methods for COVID-19 diagnosis that can be used by the public. The purpose of this research is to make a diagnosis of surveillance classification which includes PDP, ODP, and OTG using the C4.5 algorithm. The results showed that the diagnosis of the COVID-19 surveillance category using the C4.5 algorithm was successfully modeled into a decision tree with PDP, ODP, and OTG classification. The testing process in a confusion matrix with 3 (three) classes produces an accuracy rate of 92.86% which is included in the excellent classification category.

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Author Biographies

Wildan Wiguna, Universitas Bina Sarana Informatika

Information System Study Program of the City of Tasikmalaya Campus

Dwiza Riana, STMIK Nusa Mandiri, Jakarta, Indonesia

Master of Computer Science Study Program, Associate Professor at STMIK Nusa Mandiri, Jakarta, Indonesia.

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Published
2020-03-16
How to Cite
Wiguna, W., & Riana, D. (2020). DIAGNOSIS OF CORONAVIRUS DISEASE 2019 (COVID-19) SURVEILLANCE USING C4.5 ALGORITHM. Jurnal Pilar Nusa Mandiri, 16(1), 71-80. https://doi.org/10.33480/pilar.v16i1.1293
Issue
Vol 16 No 1 (2020): Pilar Nusa Mandiri : Journal of Computing and Information System Publishing Period for March 2020
Section
Articles

Copyright (c) 2020 Wildan Wiguna, Dwiza Riana

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