Forecasting COVID-19 cases for Top-3 countries of Southeast Asian Nation
Several countries continue controlling the spread of the corona virus to decrease the number of new COVID-19 cases. Currently some Southeast Asian countries require an estimate of the num-ber of daily new COVID-19 cases of in the future in order to reopen or consider lifting strict pre-vention polic...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
IIES Independent
2022-06-01
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| Series: | International Journal of Trends in Mathematics Education Research |
| Subjects: | |
| Online Access: | https://ijtmer.saintispub.com/ijtmer/article/view/138 |
| _version_ | 1828000487857717248 |
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| author | Hedi Hedi Anie Lusiani Anny Suryani Agus Binarto |
| author_facet | Hedi Hedi Anie Lusiani Anny Suryani Agus Binarto |
| author_sort | Hedi Hedi |
| collection | DOAJ |
| description | Several countries continue controlling the spread of the corona virus to decrease the number of new COVID-19 cases. Currently some Southeast Asian countries require an estimate of the num-ber of daily new COVID-19 cases of in the future in order to reopen or consider lifting strict pre-vention policies. This study applies ARIMA and SARIMA forecasting models to predict the de-cline in the number of new cases in three Southeast Asian countries. The first modelling is carried out using the ARIMA model with optimized model parameters based on the Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC) analysis. Then, the Mean Absolute Error (MAE), Root Mean Square Error (RMSE) and Mean Absolute Percent Error (MAPE) are evaluated is applied a criterion to select the best model. The best ARIMA and SARIMA models are selected manually and they are used to predict the number of new cases in three Southeast Asian coun-tries. It is expected that the number of new cases in these countries will experience a significant decline in the next month from September 2021. The prediction of SARIMA model indicates a better result than the ARIMA model which confirms the existence of a season in COVID-19 data. |
| first_indexed | 2024-04-10T06:15:10Z |
| format | Article |
| id | doaj.art-6dce8a3365c148cba71e59ecf461889b |
| institution | Directory Open Access Journal |
| issn | 2621-8488 |
| language | English |
| last_indexed | 2024-04-10T06:15:10Z |
| publishDate | 2022-06-01 |
| publisher | IIES Independent |
| record_format | Article |
| series | International Journal of Trends in Mathematics Education Research |
| spelling | doaj.art-6dce8a3365c148cba71e59ecf461889b2023-03-02T09:05:06ZengIIES IndependentInternational Journal of Trends in Mathematics Education Research2621-84882022-06-015219119810.33122/ijtmer.v5i2.138111Forecasting COVID-19 cases for Top-3 countries of Southeast Asian NationHedi Hedi0Anie Lusiani1Anny Suryani2Agus Binarto3Department of Energy Conversion Engineering, Politeknik Negeri BandungDepartment of Mechanical Engineering, Politeknik Negeri BandungDepartment of Accounting, Politeknik Negeri BandungDepartment of Electrical Electronic Engineering, Politeknik Negeri BandungSeveral countries continue controlling the spread of the corona virus to decrease the number of new COVID-19 cases. Currently some Southeast Asian countries require an estimate of the num-ber of daily new COVID-19 cases of in the future in order to reopen or consider lifting strict pre-vention policies. This study applies ARIMA and SARIMA forecasting models to predict the de-cline in the number of new cases in three Southeast Asian countries. The first modelling is carried out using the ARIMA model with optimized model parameters based on the Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC) analysis. Then, the Mean Absolute Error (MAE), Root Mean Square Error (RMSE) and Mean Absolute Percent Error (MAPE) are evaluated is applied a criterion to select the best model. The best ARIMA and SARIMA models are selected manually and they are used to predict the number of new cases in three Southeast Asian coun-tries. It is expected that the number of new cases in these countries will experience a significant decline in the next month from September 2021. The prediction of SARIMA model indicates a better result than the ARIMA model which confirms the existence of a season in COVID-19 data.https://ijtmer.saintispub.com/ijtmer/article/view/138covid-19arimasarimaprediction |
| spellingShingle | Hedi Hedi Anie Lusiani Anny Suryani Agus Binarto Forecasting COVID-19 cases for Top-3 countries of Southeast Asian Nation International Journal of Trends in Mathematics Education Research covid-19 arima sarima prediction |
| title | Forecasting COVID-19 cases for Top-3 countries of Southeast Asian Nation |
| title_full | Forecasting COVID-19 cases for Top-3 countries of Southeast Asian Nation |
| title_fullStr | Forecasting COVID-19 cases for Top-3 countries of Southeast Asian Nation |
| title_full_unstemmed | Forecasting COVID-19 cases for Top-3 countries of Southeast Asian Nation |
| title_short | Forecasting COVID-19 cases for Top-3 countries of Southeast Asian Nation |
| title_sort | forecasting covid 19 cases for top 3 countries of southeast asian nation |
| topic | covid-19 arima sarima prediction |
| url | https://ijtmer.saintispub.com/ijtmer/article/view/138 |
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