Forecast of COVID-19 Cases in Indonesia with the Triple Exponential Smoothing Algorithm

Authors

  • Ruliyanta Ruliyanta Program Studi Teknik Elektro, Universitas Nasional, Jakarta
  • Endang Retno Nugroho Profgram Studi Teknik Elektro, Universitas Nasional

DOI:

https://doi.org/10.47313/jig.v23i2.933

Keywords:

forecast, algorithm, triple exponential smoothing, COVID-19, coronavirus

Abstract

The Coronavirus (SARS-CoV-2), also known as COVID-19, has brought a worldwide threat to the living. The whole world is making extraordinary efforts to combat the spread of this deadly disease in terms of infrastructure, finances, data sources, protective equipment, life risk treatment, and several other resources. Artificial intelligence researchers focus their knowledge of expertise on developing mathematical models to analyze this epidemic situation using shared national data. To contribute to the welfare of the living community, this article proposes to utilize the Triple Exponential Smoothing algorithm to predict the development of COVID-19 throughout the country by utilizing real-time information from the Task Force for the Acceleration of Handling of Coronavirus Disease 2019 in Indonesia. Based on forecasting results, in Indonesia by the end of 2020, COVID-19 will continue to grow significantly, the number of confirmed COVID-19 people is 386,571 people with a death toll of 15,622.

References

W. World Health Organization, “WHO Director-General’s opening remarks at the media briefing on COVID-19 - 11 March 2020,” WHO Director General’s speeches, no. March, p. 4, 2020.

World Health Organization (WHO), “Coronavirus disease 2019 Situation Report 51 11th March 2020,” World Health Organization, vol. 2019, no. March, p. 2633, 2020.

World Health Organization, “Transmission of SARS-CoV-2: implications for infection prevention precautions. Scientific brief, 09 July 2020,” vol. 19, pp. 1–20, 2020.

World Health Organization(WHO), “Infection prevention and control of epidemic- and pandemic-prone acute respiratory infections in health care,” WHO Guidelines, pp. 1–156, 2014.

Organización Mundial de la Salud, “Advice on the use of masks in the context of COVID-19: interim guidance-2,” Guía Interna de la OMS, no. April, pp. 1–5, 2020.

L. Morawska and J. Cao, “Airborne transmission of SARS-CoV-2: The world should face the reality,” L. Morawska and J. Cao Environment International 139 (2020) 105730, no. January 2020.

COVID-19 Community Mobility Report, “Indonesia Mobility changes,” google.com/covid19/mobility, no. July 12, 2020.

J. N. Dhanwant and V. Ramanathan, “Forecasting COVID 19 growth in India using Susceptible-Infected-Recovered (S.I.R) model,” 2020.

F. A. M. Cássaro and L. F. Pires, “Can we predict the occurrence of COVID-19 cases? Considerations using a simple model of growth,” Science of the Total Environment, vol. 728, 2020.

R. Gupta, S. K. Pal, and G. Pandey, “A Comprehensive Analysis of COVID-19 Outbreak situation in India,” medRxiv, p. 2020.04.08.20058347, 2020.

F. Siskus and D. Arianto, “Prediksi Kasus Covid-19 Di Indonesia Menggunakan Metode Backpropagation Dan Fuzzy Tsukamoto,” Jurnal Teknologi Informasi, vol. 4, no. 1, 2020.

W. C. Culp, “Coronavirus Disease 2019,” A & A Practice, vol. 14, no. 6, p. e01218, 2020.

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Published

2020-11-17