Browsing by Author "Sabrillian, Nickhallen"

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    KLASTERISASI LOKASI TINGKAT PENYEBARAN COVID-19 MENGGUNAKAN ALGORITMA K-MEANS
    (Elfitra, 2022-07) Sabrillian, Nickhallen; Alfirman, Alfirman
    Disease is a bad condition in specific organs or body parts caused by harmful microorganisms such as bacteria, viruses, wounds, chemical imbalances in the body, exposure to toxins, and the appearance of imperfect cells. From 2020 until now, Indonesia has been shocked about the spread of a fairly serious disease. The case was caused by the coronavirus, known as covid-19 (Corona Virus Disease-2019). The spread of the Covid-19 virus is swift. Human-to-human transmission occurs near an infected person. The main transmission is an infected person sneezing and respiratory droplets such as influenza, the oral or nasal mucosa, and the lungs of people who breathe infected air. The government has issued various policies to minimize the spread of COVID-19 by imposing social distancing, physical distancing, large-scale social restrictions (PSBB), and restrictions on community activities (PPKM) in several areas. Problems arise that make it difficult for the Health Office to group areas that will produce the central points for the spread of COVID-19 sufferers, so data is grouped based on the number of sufferers. This study aimed to determine the regional grouping of the spread of COVID-19 in Pekanbaru City. The data used is data on positive cases of COVID-19 obtained from the Pekanbaru City Health Office and data on the number of residents in Pekanbaru City based on 83 villages. The method used in this research is K-Means Clustering. K-Means Clustering is a method that can group areas with the potential for COVID-19. Based on the research results, there are 46 villages in cluster 1, 7 villages in cluster 2 and 30 villages in cluster 3.