Big Data Analytics in Healthcare: COVID-19 Indonesia Clustering
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Keywords
Big Data, Big Data Analytics, Data Mining, COVID-19, Clustering, k-means algorithm
Abstract
The rapid growth of the Internet and Technology produced a massive amount of data that resulted a phenomenon called Big Data. To process such a complex kind of massive amount of data, an advanced approach and tool is needed that is able to quickly produce results. This approach to analyzing massive amount of data is known as Big Data Analytics. Big data analytics is widely used in various sectors, not to mention the health sector. In the healthcare sector, recently there has been a study that is often carried out in dealing with crisis situations, namely research on implementing big data analytics to provide technological solutions to help deal with pandemics. In this article, we analyze and visualize the data collected from Indonesia. The data analyzed starts from the first case of COVID-19 in Indonesia to present. The proposed solution is to classify the regional case data into a group that can represent the situation of the area. As a result, it is determined based on the data that there are three groups consisting of areas with low risk, moderate risk, and high risk. In addition, this article proposes combining big data analytics technology with cloud technology to facilitate the dissemination of information to citizens to increase awareness about the spread of the COVID-19 virus.
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