Pengelompokan Provinsi Di Indonesia Berdasarkan Data Covid-19 Menggunakan Algoritma K-Means
Abstract
COVID-19 is a disease caused by a coronavirus. The disease that initially
only spread in China has now spread quickly to Indonesia and was declared a
pandemic. Transmission occurs related to the density of the environment,
cleanliness, and health conditions of the body. Based on this, various policies
were made in handling COVID-19 in Indonesia. As an effort to prevent
transmission, based on this, social distancing is carried out, maintaining
cleanliness by washing hands, and maintaining health. In addition, one of the
efforts that can be made is to study the characteristics of the COVID-19 data and
group them based on similar characteristics in each province in Indonesia so that
the characteristics of each group can be identified. One way of grouping that is
commonly used is clustering. Clustering is grouping observations into object
classes that are similar or similar to one another and different from groups in
other object classes. The clustering method that is often used is the K-Means
method. K-means is very well known for its ease and ability to segment large data
very quickly. So in this study K-Means clustering was used on COVID-19 case
data with the variables used namely cases of death, cases still sick, and cases
recovered from COVID-19.
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