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Abstract
The COVID-19 epidemic has spread throughout countries around the world. In Indonesia, this case was detected in early March 2020, and until now, there is still an increase in positive cases of COVID-19. The purpose of this paper is to predict COVID-19 cases in Indonesia using a time series approach. The method used is H-WEMA method because this method can capture trend data patterns following the conditions of COVID-19 cases in Indonesia. Based on the analysis results, H-WEMA can predict COVID-19 cases very well. The forecasted results of the COVID-19 cases in Indonesia still have an upward trend, so it needs the cooperation of all elements of community to reduce the spread of COVID-19.
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References
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References
Yuliana, "Corona Virus Disease (Covid-19); Sebuah Tinjauan Literatur," Wellness and Healthy Magazine, vol. 2, no. 1, pp. 187-192, 2020.
C. Huang, Y. Wang, X. Li, L. Ren, J. Zhao, Y. Hu, L. Zhang, G. Fan, J. Xu, X. Gu, Z. Cheng, T. Yu, J. Xia, Y. Wei, W. Wu, X. Xie, W. Yin, H. Li, M. Liu, Y. Xiao, . H. Gao, L. Guo, J. Xie, G. Wang, R. Jiang, Z. Gao, Q. Jin, J. Wang and B. Cao, "Clinical Features of Patients Infected with 2019 Novel Coronavirus in Wuhan, China," Lancet, vol. 395, pp. 497-506, 2020.
Worldometer, "COVID-19 Coronavirus Pandemic," Worldometer, 1 September 2021. [Online]. Available: https://www.worldometers.info/coronavirus/. [Accessed 1 September 2021].
Satuan Tugas Penanganan COVID-19, "Peta Sebaran COVID-19," Komite Penanganan COVID-19 dan Pemulihan Ekonomi Nasional, 1 September 2021. [Online]. Available: https://covid19.go.id/peta-sebaran-covid19. [Accessed 1 September 2021].
A. K. Sahai, N. Rath and M. P. Singh, "ARIMA Modelling and Forecasting of COVID-19 in Top Five Affected," Diabetes and Metabolic Syndrome: Clinical Reserarch and Reviews, vol. 14, pp. 1419-1427, 2020.
I. Kirbas, A. Sozen, A. D. Tuncer and F. S. Kazancioglu, "Comparative Analysis and Forecasting of COVID-19 Cases in Various European Countries with ARIMA, NARNN and LSTM Approaches," Chaos, Solitons and Fractals, vol. 138, 2020.
X. Duan and X. Zhang, "ARIMA Modelling and Forecasting of Irregularly Patterned COVID-19 Outbreaks using Japanese and South Korean data," Data in Brief, vol. 31, 2020.
S. I. Alzahrani, I. A. Aljamaan and E. A. Al-Fakih, "Forecasting the Spread of the COVID-19 Pandemic in Saudi Arabia using ARIMA Prediction Model Under Current Public Health Interventions," Journal of Infection and Public Health, vol. 13, no. 7, pp. 914-919, 2020.
D. Guleryuz, "Forecasting Outbreak of COVID-19 in Turkey; Comparison of Box–Jenkins, Brown’s Exponential Smoothing and Long Short-Term Memory Models," Process Safety and Environmental Protection, vol. 149, pp. 927-935, 2021.
F. M. Khan and R. Gupta, "ARIMA and NAR Based Prediction Model for Time Series Analysis of COVID-19 Cases in India," Journal of Safety Science and Resilience, vol. 1, no. 1, pp. 12-18, 2020.
D. Benvenuto, M. Giovanetti, L. Vasallo, S. Angeletti and M. Ciccozzi, "Application of the ARIMA Model on the COVID-2019 Epidemic Dataset," Data in Brief, vol. 29, 2020.
Z. E. Rasjid, R. Setiawan and R. Effendi, "A Comparison: Prediction of Death and Infected COVID-19 Cases in Indonesia Using Time Series Smoothing and LSTM Neural Network," Procedia Computer Science, vol. 179, pp. 982-988, 2021.
C. B. A. Satrio, W. Darmawan, B. U. Nadia and N. Hanafiah, "Time Series Analysis and Forecasting of Coronavirus Disease in Indonesia Using ARIMA Model and PROPHET," Procedia Computer Science, vol. 179, pp. 524-532, 2021.
A. Hernandez-Matamoroz, H. Fujita, T. Hayashi and H. Perez-Meana, "Forecasting of COVID19 per Regions Using ARIMA Models and Polynomial Functions," Applied Soft Computing, vol. 96, 2020.
M. S. Hossain, S. Ahmed and M. J. Uddin, "Impact of Weather on COVID-19 Transmission in South Asian Countries: An Application of the ARIMAX Model," Science of The Total Environment, vol. 761, 2021.
S. Makridakis, S. C. Wheelwright and V. E. McGee, Forecasting: Methods and Applications, Canada: John Wiley & Sons, Inc, 1983.
S. Hansun and Subanar, "H-WEMA: A New Approach of Double Exponential Smoothing Method," Telkomnika, vol. 14, no. 2, pp. 772-777, 2016.
D. C. Montgomery, C. L. Jennings and M. Kulahci, Introduction to Time Series Analysis and Forecasting, Canada: John Wiley & Sons, Inc, 2015.
Kawal COVID-19, "Kawal informasi seputar COVID-19 secara tepat dan akurat," Kawal COVID-19, 1 September 2021. [Online]. Available: https://kawalcovid19.id/. [Accessed 1 September 2021].
J. J. M. Moreno, A. P. Pol, A. S. Abad and B. C. Blasco, "Using the R-MAPE index as a resistant measure of forecast accuracy," Psicothema, vol. 25, no. 4, pp. 500-506, 2013.