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All Journal JOIV : International Journal on Informatics Visualization Journal of Applied Science, Engineering, Technology, and Education
Eva Boj
Department of Economic, Financial and Actuarial Mathematics, Faculty of Economics and Business, Universitat de Barcelona, Spain
Civil Engineering, Building, Construction & Architecture Computer Science & IT Electrical & Electronics Engineering Industrial & Manufacturing Engineering Other

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Application of Neural Network Time Series (NNAR) and ARIMA to Forecast Infection Fatality Rate (IFR) of COVID-19 in Brazil Ansari Saleh Ahmar; Eva Boj
JOIV : International Journal on Informatics Visualization Vol 5, No 1 (2021)
Publisher : Politeknik Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.5.1.372

Abstract

Forecasting is a method that is often used to view future events using past time data. Past time data have useful information to use in obtaining the future. The aim of this study was to forecast infection fatality rate (IFR) of COVID-19 in Brazil using NNAR and ARIMA. ARIMA and NNAR are used because (1) ARIMA is a simple stochastic time series method that can be used to train and predict future time points and ARIMA also capable of capturing dynamic interactions when it uses error terms and observations of lagged terms; (2) the Artificial Neural Network (ANN) is a technique capable of analyzing certain non-linear interactions between input regressor and responses, and Neural Network Time Series (NNAR) is one method of ANN in which lagged time series values were used as inputs to a neural network. Data included in this study were derived from the total data of confirmed cases and the total data of death of COVID-19. The data of COVID-19 in Brazil from February 15, 2020 to April 30, 2020 were collected from the Worldometer (https://www.worldometers.info/coronavirus/) and Microsoft Excel 2013 was used to build a time-series table. Forecasting was accomplished by means of a time series package (forecast package) in R Software.  Neural Network Time Series and ARIMA models were applied to a dataset consisting of 76 days. The accuracy of forecasting was examined by means of an MSE. The forecast of IFR of COVID-19 in Brazil from May 01, 2020 to May 10, 2020 with NNAR (1,1) model was around in 6,85% and ARIMA (0,2,1) was around in 7.11%.
The date predicted 200.000 cases of Covid-19 in Spain Ansari Saleh Ahmar; Eva Boj
Journal of Applied Science, Engineering, Technology, and Education Vol. 2 No. 2 (2020)
Publisher : Yayasan Ahmar Cendekia Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (483.471 KB) | DOI: 10.35877/454RI.asci22102

Abstract

The aim of this study is to predict 200.000 cases of Covid-19 in Spain. Covid-19 Spanish confirmed data obtained from Worldometer from 01 March 2020 – 17 April 2020. The data from 01 March 2020 – 10 April 2020 using to fitting with data from 11 April – 17 April 2020. For the evaluation of the forecasting accuracy measures, we use the mean absolute percentage error (MAPE). Based on the results of SutteARIMA fitting data, the accuracy of SutteARIMA for the period 11 April 2020 - 17 April 2020 is 0.61% and we forecast 20.000 confirmed cases of Spain by the WHO situation report day 90/91 which is 19 April 2020 / 20 April 2020.
Co-Authors Ahmar, Ansari Saleh