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Evaluation of forecast performance of COVID-19 with different time horizons / Amirul Rashid Che Samsol and Azlan Abdul Aziz

The first wave of the disease in Malaysia from 25 January to 16 February 2020 involved 22 cases. Accurate forecasting of COVID-19 case movements is crucial for the preparedness of the country’s health systems in terms of outbreak management and resource planning. The study's main goal is to gen...

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محفوظ في:
التفاصيل البيبلوغرافية
المؤلفون الرئيسيون: Che Samsol, Amirul Rashid, Abdul Aziz, Azlan
التنسيق: Book Section
اللغة:English
منشور في: College of Computing, Informatics and Media, UiTM Perlis 2023
الموضوعات:
Time-series analysis
الوصول للمادة أونلاين:https://ir.uitm.edu.my/id/eprint/100729/1/100729.pdf
https://ir.uitm.edu.my/id/eprint/100729/
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id my.uitm.ir.100729
record_format eprints
spelling my.uitm.ir.1007292024-09-27T01:38:35Z https://ir.uitm.edu.my/id/eprint/100729/ Evaluation of forecast performance of COVID-19 with different time horizons / Amirul Rashid Che Samsol and Azlan Abdul Aziz Che Samsol, Amirul Rashid Abdul Aziz, Azlan Time-series analysis The first wave of the disease in Malaysia from 25 January to 16 February 2020 involved 22 cases. Accurate forecasting of COVID-19 case movements is crucial for the preparedness of the country’s health systems in terms of outbreak management and resource planning. The study's main goal is to generate the forecast values for COVID-19 cases in Malaysia by using forecasting models Data from the Malaysia's Ministry of Health (MOH) have been obtained from 2020 to 2022 with 1016 observations. This study aims to determine the best "win" model and produce forecast values by using Time-series Cross-Validation. Five models and three error measures have been implemented in this study. There are Naïve model, Mean Model, Single Exponential Smoothing Technique, Holt's method, and Box-Jenkins model. While the error measures used are Root Mean Square Error (RMSE), and Mean Absolute Error (MAE) and Mean Absolute Scale Error (MASE). To execute these models, RStudio software is based on R programming language 4.2.2. The results show that the best "win" model for COVID-19 cases in Malaysia is Naïve model, Single Exponential Smoothing Technique, Holt’s Method and ARIMA(0,0,0) and mean model, respectively. The finding of this study will improve Malaysians’ decisions and awareness. College of Computing, Informatics and Media, UiTM Perlis 2023 Book Section PeerReviewed text en https://ir.uitm.edu.my/id/eprint/100729/1/100729.pdf Evaluation of forecast performance of COVID-19 with different time horizons / Amirul Rashid Che Samsol and Azlan Abdul Aziz. (2023) In: Research Exhibition in Mathematics and Computer Sciences (REMACS 5.0). College of Computing, Informatics and Media, UiTM Perlis, pp. 115-116. ISBN 978-629-97934-0-3
institution Universiti Teknologi Mara
building Tun Abdul Razak Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Mara
content_source UiTM Institutional Repository
url_provider http://ir.uitm.edu.my/
language English
topic Time-series analysis
spellingShingle Time-series analysis
Che Samsol, Amirul Rashid
Abdul Aziz, Azlan
Evaluation of forecast performance of COVID-19 with different time horizons / Amirul Rashid Che Samsol and Azlan Abdul Aziz
description The first wave of the disease in Malaysia from 25 January to 16 February 2020 involved 22 cases. Accurate forecasting of COVID-19 case movements is crucial for the preparedness of the country’s health systems in terms of outbreak management and resource planning. The study's main goal is to generate the forecast values for COVID-19 cases in Malaysia by using forecasting models Data from the Malaysia's Ministry of Health (MOH) have been obtained from 2020 to 2022 with 1016 observations. This study aims to determine the best "win" model and produce forecast values by using Time-series Cross-Validation. Five models and three error measures have been implemented in this study. There are Naïve model, Mean Model, Single Exponential Smoothing Technique, Holt's method, and Box-Jenkins model. While the error measures used are Root Mean Square Error (RMSE), and Mean Absolute Error (MAE) and Mean Absolute Scale Error (MASE). To execute these models, RStudio software is based on R programming language 4.2.2. The results show that the best "win" model for COVID-19 cases in Malaysia is Naïve model, Single Exponential Smoothing Technique, Holt’s Method and ARIMA(0,0,0) and mean model, respectively. The finding of this study will improve Malaysians’ decisions and awareness.
format Book Section
author Che Samsol, Amirul Rashid
Abdul Aziz, Azlan
author_facet Che Samsol, Amirul Rashid
Abdul Aziz, Azlan
author_sort Che Samsol, Amirul Rashid
title Evaluation of forecast performance of COVID-19 with different time horizons / Amirul Rashid Che Samsol and Azlan Abdul Aziz
title_short Evaluation of forecast performance of COVID-19 with different time horizons / Amirul Rashid Che Samsol and Azlan Abdul Aziz
title_full Evaluation of forecast performance of COVID-19 with different time horizons / Amirul Rashid Che Samsol and Azlan Abdul Aziz
title_fullStr Evaluation of forecast performance of COVID-19 with different time horizons / Amirul Rashid Che Samsol and Azlan Abdul Aziz
title_full_unstemmed Evaluation of forecast performance of COVID-19 with different time horizons / Amirul Rashid Che Samsol and Azlan Abdul Aziz
title_sort evaluation of forecast performance of covid-19 with different time horizons / amirul rashid che samsol and azlan abdul aziz
publisher College of Computing, Informatics and Media, UiTM Perlis
publishDate 2023
url https://ir.uitm.edu.my/id/eprint/100729/1/100729.pdf
https://ir.uitm.edu.my/id/eprint/100729/
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score 13.251813

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