Visualisation System of COVID-19 Data in Malaysia

Rehman Ullah, Khan and NOR SYAZA, SYAMIMI and CLADIA SIMBUT, MAMBANG and IVY, THOMAS and NI WEE, TZI (2021) Visualisation System of COVID-19 Data in Malaysia. Trends in Undergraduate Research, 4 (1). pp. 8-17.

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Abstract

Pandemics are highly unlikely events, therefore, we need a system to understand the statistics about the pandamic. Machine learning algorithms can analyse the data and then we can plan for handling the pandamic. To date, many people are suffering because of the lack of reliable information system. The problem is that there is no integrated system to use the data and plan for pandemic management to minimise social panic. This study aims to provide a system, using COVID-19 data as a sample to visualise and analyse cases, deaths, discharged ICU cases updates in Malaysia as a whole state wise of COVID-19 daily statistics. The results provide visualisation and case comparison among states in Malaysia to easily and quickly understand the situation. This will help and assist the management in decision-making.

Item Type: Article
Uncontrolled Keywords: COVID-19, Decision support system, Disaster management, Panic, Pandemic, University, UNIMAS, Borneo, Malaysia, Sarawak, Kuching, Samarahan, education, IPTA, Universiti Malaysia Sarawak
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Q Science > QA Mathematics > QA76 Computer software
Divisions: Academic Faculties, Institutes and Centres > Faculty of Cognitive Sciences and Human Development
Depositing User: Sanawi
Date Deposited: 02 Jul 2021 05:45
Last Modified: 02 Jul 2021 05:45
URI: http://ir.unimas.my/id/eprint/35544

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