Data Analysis of Covid-19 Pandemic in Malaysia and Singapore

Tang, Nelson, Kwong Kin and Chong, Jiet Vun and Baek, Dae Hui and Wong, Jeng Yang and Dini, Handayani (2021) Data Analysis of Covid-19 Pandemic in Malaysia and Singapore. Journal of Data Science, 2021 (03). ISSN 2805-5160

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COVID-19, an infectious disease that was caused by a newly discovered coronavirus. According to the World Health Organization (WHO), it will affect the human lung and airways hard to be moderated. The COVID-19 virus can spread through saliva drops or be released from the nose when an infected person coughs or sneezes. By washing hands or rubbing alcohol-based often and avoiding touching the face, one can prevent infection or slow down the spread rate. Currently, there are no specific vaccines or treatments for COVID-19. Some datasets are generated from COVID-19 epidemic in Malaysia and Singapore and the datasets can be used for analysis to improve understanding of the COVID-19. In this project, six datasets are collected and conducted with data selection, data pre-processing, data transformation, and data mining. To conduct visualization and analysis of the datasets, Microsoft Azure Machine Learning Studio is used during the methodology part while Microsoft Excel and R Studio are used to generate five different graphs based on the datasets. The objective of this project is to compare, investigate and analyse the COVID-19 epidemic and find out the impact of Movement Control Order (MCO) in Malaysia and Circuit Breaker (CB) in Singapore to overcome the COVID-19 epidemic in both countries based on the data visualization and analysis in this project.

Item Type: Article
Uncontrolled Keywords: Data Analysis, Covid19 Pandemic, Movement Control Order, Circuit Breaker
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Q Science > QA Mathematics > QA76 Computer software
Depositing User: Unnamed user with email
Date Deposited: 25 Aug 2021 06:34
Last Modified: 26 Aug 2021 10:31

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