Data Analysis of Covid-19 Pandemic in Malaysia and Singapore

• Main Authors: Tang, Nelson, Kwong Kin, Chong, Jiet Vun, Baek, Dae Hui, Wong, Jeng Yang, Dini, Handayani
• Format: Article
• Language: English
• Published: INTI International University 2021
• Subjects: QA75 Electronic computers. Computer science; QA76 Computer software
• Online Access: http://eprints.intimal.edu.my/1526/1/vol.2021_003.pdf; http://eprints.intimal.edu.my/1526/; https://ipublishing.intimal.edu.my/jods.html

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.