Proceedings of the 2nd International Seminar of Science and Applied Technology (ISSAT 2021)

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Forecasting the Number of New Cases of COVID-19 in Indonesia Using the ARIMA and SARIMA Prediction Models

Authors
Hedi1, *, Anny Suryani2, Agus Binarto3
1Energy Conversion Engineering Department, Politeknik Negeri Bandung, Indonesia
2Accounting Department, Politeknik Negeri Bandung, Indonesia
3Electrical Electronic Engineering Department, Politeknik Negeri Bandung, Indonesia
*Corresponding author. Email: hedi@polban.ac.id
Corresponding Author
Hedi
Available Online 23 November 2021.
DOI
10.2991/aer.k.211106.011How to use a DOI?
Keywords
COVID-19; ARIMA; SARIMA; Forecasting
Abstract

In June 2020, the Indonesian Government announced to implement a new normal policy as a result of the increasing number of new cases of coronavirus disease (COVID-19) every day, but many new cases until August 2021 were still above June 2020. To control the spread of this pandemic, the Government implements a limiting community activities policy. For this reason, to predict the success of this policy forecasting many new cases in the future is necessary. The purpose of this study is to provide the estimated number of COVID-19 new cases in Indonesia. This study applies two mathematical models: Autoregressive Integrated Moving Average (ARIMA) and Seasonal ARIMA (SARIMA). This research method begins with determining the source of the data. Based on daily observation data from July 25, 2020 to September 9, 2021, identification and estimation of ARIMA and SARIMA modeling were carried out. Based on the calculation results of Akaike’s Information Criterion (AIC) and Bayesian Information Criterion (BIC), ARIMA (5, 1, 4) and SARIMA (2, 1, 2)(0, 1, 1)7 are the most suitable model. Furthermore, based on the calculation results of the smallest Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), and Mean Absolute Percent Error (MAPE), the ARIMA(5, 1, 4) model is the most suitable forecasting model for the number of new COVID-19 cases in Indonesia

Copyright
© 2021 The Authors. Published by Atlantis Press International B.V.
Open Access
This is an open access article under the CC BY-NC license.

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Volume Title
Proceedings of the 2nd International Seminar of Science and Applied Technology (ISSAT 2021)
Series
Advances in Engineering Research
Publication Date
23 November 2021
ISBN
978-94-6239-451-3
ISSN
2352-5401
DOI
10.2991/aer.k.211106.011How to use a DOI?
Copyright
© 2021 The Authors. Published by Atlantis Press International B.V.
Open Access
This is an open access article under the CC BY-NC license.

Cite this article

risenwbib
TY  - CONF
AU  - Hedi
AU  - Anny Suryani
AU  - Agus Binarto
PY  - 2021
DA  - 2021/11/23
TI  - Forecasting the Number of New Cases of COVID-19 in Indonesia Using the ARIMA and SARIMA Prediction Models
BT  - Proceedings of the 2nd International Seminar of Science and Applied Technology (ISSAT 2021)
PB  - Atlantis Press
SP  - 63
EP  - 68
SN  - 2352-5401
UR  - https://doi.org/10.2991/aer.k.211106.011
DO  - 10.2991/aer.k.211106.011
ID  - 2021
ER  -