Penerapan Algoritma K-Means Untuk Mengelompokkan provinsi Di Indonesia Berdasarkan Data Sebaran Covid-19 - Achmad Furqon Nur Fitriadhi; Retno Wahyusari (Jurusan Informatika STTR Cepu, 2022)
In December 2019 in Wuhan, China there was an outbreak that attacked the respiratory tract. Early in January, WHO identified the virus as Coronavirus or 2019-nCoV which later announced the official name for the virus that was ravaging COVID-19. The COVID-19 virus did not only occur in Wuhan, but also spread throughout the world. This is no exception in Indonesia, from March to April the graph data has increased significantly. The purpose of this study is to apply the K-Means algorithm in grouping provinces based on the level of spread of the Corona virus (COVID-19). The research carried out is up-to-date by adding attributes in group determination, the attributes used are the number of positives, the number of recoveries and the number of deaths. The study resulted in 2 (two) groups with cluster 0 membership indicating the area that was least affected by COVID-19 with a total of 6 data, and cluster 1 showing the area most affected by COVID-19 with a total of 28 data. From this research, it can be concluded that the government should carry out handling of COVID-19 more focused on cluster 1 which has the largest number of impacts.