COVID-19 Cases and Deaths in Southeast Asia Clustering using K-Means Algorithm
Juniar Hutagalung, Ni Luh Wiwik Sri Rahayu Ginantra, Gita Widi Bhawika, Wayan Gede Suka Parwita, Anjar Wanto, Pawer Darasa Panjaitan
Abstract
Abstract Covid-19 is an infectious illness caused by a newly identified form of coronavirus. This is a new virus and illness that was previously unknown before the December 2019 outbreak in Wuhan, China. The number of confirmed cases of Covid-19 and the number of deaths due to this virus in Southeast Asia are increasing and quite alarming. Therefore this study will discuss the grouping of Cases and Deaths of COVID-19 in Southeast Asia. The method used is the K-Means Clustering Data Mining. By using this method the data that has been obtained can be grouped into several clusters, where K-Means Clustering Process is applied using RapidMiner tools. Data used are Country statistics, Area of recorded laboratory-confirmed cases of COVID-19, and April 2020 deaths from WHO (World Health Organization). Data is divided into 3 clusters: high (C1), medium (C2) and low (C3). The results obtained are that there are four countries with a high level cluster (C1), one country with a moderate level cluster (C2), and 6 countries with a low level cluster (C3). This can be an input for each country to increase awareness of the transmission of Covid-19.