Forecasting the spread of Covid-19 Pandemic in Malaysia / Wan Muhammad Qawiem Wan Sulaiman, Nuratikah Rosli and Miza Filza Farisa Ismail

Wan Sulaiman, Wan Muhammad Qawiem and Rosli, Nuratikah and Ismail, Miza Filza Farisa (2021) Forecasting the spread of Covid-19 Pandemic in Malaysia / Wan Muhammad Qawiem Wan Sulaiman, Nuratikah Rosli and Miza Filza Farisa Ismail. [Student Project] (Unpublished)

Abstract

COVID-19 is rapidly expanding across the globe. Malaysia, as a Southeast Asian region, has also been affected by COVID-19. Since the COVID-19 outbreak first emerged in China at the end of 2019, Malaysia has taken precautionary measures to prevent it from entering the nation. However, since COVID-19 is more than certainly unstoppable, Malaysia eventually received the first case of it in early January 2020. Hence, this research claims to look at the number of COVID-19 daily new confirmed cases in Malaysia, analyze the best model for forecasting and forecast the number of COVID-19 daily new cases starting on 1 April 2021 and ahead. For this research, the number of daily confirmed new cases of COVID-19 in Malaysia from 15 March 2020 to 31 March 2021 was estimated and forecasts using the curve estimation models such as Holt’s method, double exponential smoothing (DES) and the Box-Jenkins approach, ARIMA model. Besides, COVID-19 daily confirmed cases data retrieved from the Ministry of Health (MOH). The study’s findings indicate that ARIMA(1,1,3) is the preferred model for forecasting since it has the smallest values of error measures for Root Mean Squared Error (RMSE), Mean Absolute Error (MAE) and Mean Absolute Percentage Error (MAPE) as compared to other models. In conclusion, subsequent studies would likely yield more discoveries and a more systematic approach to have better and accurate forecasting.

Metadata

Item Type: Student Project
Creators:
Creators
Email / ID Num.
Wan Sulaiman, Wan Muhammad Qawiem
UNSPECIFIED
Rosli, Nuratikah
UNSPECIFIED
Ismail, Miza Filza Farisa
UNSPECIFIED
Contributors:
Contribution
Name
Email / ID Num.
Thesis advisor
Ab Malek, Isnewati
UNSPECIFIED
Subjects: H Social Sciences > HA Statistics
H Social Sciences > HA Statistics > Statistical data
H Social Sciences > HA Statistics > Theory and method of social science statistics > Surveys. Sampling. Statistical survey methodology
H Social Sciences > HA Statistics > Theory and method of social science statistics > Data envelopment analysis
Divisions: Universiti Teknologi MARA, Negeri Sembilan > Seremban Campus > Faculty of Computer and Mathematical Sciences
Programme: Bachelor of Science (Hons.) Statistics
Keywords: Covid-19 Pandemic, Malaysia, China
Date: 2021
URI: https://ir.uitm.edu.my/id/eprint/59480
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