Implementasi Algoritma K-Means Dalam Menentukan Tingkat Penyebaran Pandemi Covid-19 Di Sumatera Barat

Penulis

  • STMIK JAYANUSA PADANG

DOI:

https://doi.org/10.33884/cbis.v9i1.5459

Kata Kunci:

Data Mining, K-Means, covid-19

Abstrak

Corona viruses (CoV) are part of a family of viruses that cause illnesses ranging from the flu to more severe illnesses such as Middle East Respiratory Syndrome (MERS-CoV) and Severe Acute Respiratory Syndrome (SARS-CoV). This virus can be transmitted from person to person through small droplets from the nose or mouth when coughing, sneezing or speaking. Because the spread of this virus is very fast, it requires fast handling so that this virus does not spread, one of which is by implementing health protocols, namely maintaining distance, washing hands and using masks. All provinces in Indonesia have not been spared from this virus, including the province of West Sumatra. Classification of the spread of this virus is necessary in order to break the chain of its spread. One of the techniques used in this grouping is k-means, which uses several groups to assign multiple data to a partition system. The results of this study indicate that the regions in the first cluster have the highest rates of positive cases and patients who die, while the areas in the second and third clusters have the potential for the spread of Covid-19 which is also a concern of the government.

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Diterbitkan

2022-02-14

Cara Mengutip

Dian Permata. (2022). Implementasi Algoritma K-Means Dalam Menentukan Tingkat Penyebaran Pandemi Covid-19 Di Sumatera Barat. Computer Based Information System Journal, 9(1). https://doi.org/10.33884/cbis.v9i1.5459

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