Application Of The Hybrid Method Nonlinear Regression With Modified Logistic Growth Model - Exponential Double Smoothing For Forecasting Covid-19 Cases In Indonesia And Armenia

Authors

  • Andy Rezky Pratama Syam Arez Mahasiswa

DOI:

https://doi.org/10.20956/jmsk.v17i2.11747

Keywords:

Covid-19, Hybrid, Logistic Growth

Abstract

Since the first cases of Covid-19 (Corona Virus Disease-19) infection were officially recognized and recorded in Indonesia on March 2, 2020 and March 1, 2020 in Armenia, the addition of new cases has not shown any indication of sloping. The relatively high number of new cases indicates that Indonesia has not yet passed the peak of the pandemic. As for Armenia, the addition of new cases indicates a new pandemic peak to be faced. In these conditions, an important question for decision makers (the Government) to find answers to is when and at what level of total cases will the COVID-19 pandemic end in Indonesia or the second wave in Armenia. Based on this, the forecasting method of Hybrid Nonlinear Regression With Modified Logistic Growth Model - Double Smoothing Exponential and Classical methods is used to predict the Covid-19 cases that occur in Indonesia and Armenia. Based on the model formed, the peak of Covid-19 cases in Indonesia is predicted to occur on November 26, 2020, with the number of cases reaching 5968 cases. As for Armenia, the peak of Covid-19 cases will occur on November 15, 2020, with the number of cases reaching 3098 cases. Covid-19 in both countries is predicted to decline and be constant in 2021. For the country, Indonesia is predicted to begin to stabilize and be controlled in July - August 2021. As for Armenia, Covid-19 is predicted to be under control and approaching 0 cases in February - March 2021.

References

Wei, W.W.S. 2006. Time Series Analysis: Univariate and Multivariate Methods, Second Edition. New York : Pearson Education

Purnama, D.I., Model Hybrid Seasonal Autoregressive Integrated Moving Average (Sarima)-Support Vector Regression (Svr) Dan Penerapannya Pada Harga Gabah Nasional

Yudaruddin, Rizky, " Forecasting untuk Kegiatan Ekonomi dan Bisnis" RV Pustaka Horizon. 2019

https://www.worldometers.info/coronavirus/country/armenia/

https://www.worldometers.info/coronavirus/country/indonesia/

J. E. Hanke, D. W. Wichern, dan A. G, Reitsch, “Peramalan Bisnis Edisi Ke-7 (terj.)”, Alih Bahasa: Anantanur, D, Klaten: PT Intan Sejati, 2005

Neter, J., Kutner, M.H., Nachtsheim, C.J. and Wasserman, W. (1996) Applied Linear Statistical Models. 4th Edition, WCB McGraw-Hill, New York

Silvester, Arista. 2019. Model Regresi Non Linear dan Penerapannya. Skripsi : Universitas Sanata Dharma Yogyakarta, Fakultas Sains dan Teknologi.

Neter, J., Kutner, M.H., Nachtsheim, C.J. and Wasserman, W. (1996) Applied Linear Statistical Models. 4th Edition, WCB McGraw-Hill, New York

S.Makridakis, S. C.Wheelwright dan V. E. McGee, “Metode dan Aplikasi Peramalan Jilid 1 Edisi Revisi (terj.)”, Alih Bahasa: Hari Suminto, Jakarta: Binapura Aksara. 1999

Faical Ndairou and Ivan Area and Juan J. Nieto and Del_m F.M. Torres, Mathematical Modeling of COVID-19 Transmission Dynamics with a Case Study of Wuhan, Chaos, Solitons & Fractals109 (2020), 109846

Bates, D. M. & Watts, D.G. (2007). Nonlinear Regression Analysis and Its Applications. New York: John Wiley & Sons

Downloads

Published

2020-12-23

How to Cite

Arez, A. R. P. S. (2020). Application Of The Hybrid Method Nonlinear Regression With Modified Logistic Growth Model - Exponential Double Smoothing For Forecasting Covid-19 Cases In Indonesia And Armenia. Jurnal Matematika, Statistika Dan Komputasi, 17(2), 252–266. https://doi.org/10.20956/jmsk.v17i2.11747

Issue

Vol. 17 No. 2 (2021): JANUARY 2021

Section

Research Articles

License

Copyright (c) 2020 Author and publisher

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.

Jurnal Matematika, Statistika dan Komputasi is an Open Access journal, all articles are distributed under the terms of the Creative Commons Attribution License, allowing third parties to copy and redistribute the material in any medium or format, transform, and build upon the material, provided the original work is properly cited and states its license.  This license allows authors and readers to use all articles, data sets, graphics and appendices in data mining applications, search engines, web sites, blogs and other platforms by providing appropriate reference.