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All Journal Jurnal Tekinkom (Teknik Informasi dan Komputer)
Tessalonika Siahaan
Universitas Prima Indonesia
Computer Science & IT

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Journal : Jurnal Tekinkom (Teknik Informasi dan Komputer)

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PENERAPAN DATA MINING CLASSIFICATION UNTUK DATA PASIEN COVID- 19 MENGGUNAKAN METODE NAÏVE BAYES Tessalonika Siahaan; Yonata Laia; Manusun Silitonga; Friska Claudia Pasaribu
Jurnal Tekinkom (Teknik Informasi dan Komputer) Vol 6 No 1 (2023)
Publisher : Politeknik Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37600/tekinkom.v6i1.879

Abstract

Covid-19 is an infectious disease caused by a new coronavirus discovered in 2019, hereafter Sars-Cov 2 (Severe Acute). Coronavirus Respiratory Syndrome 2). This virus is very small in size (120-Knowledge is participants' understanding of a given topic. Knowledge is the ability to receive, store and use information, influenced by experience and skills. This research creates a system that can help anyone who wants to know what causes are behind the increasing spread of bacteria in the form of viruses. Therefore, it is necessary to find out what factors have caused the increase in the number of people infected with this deadly virus. Using the Naive Bayes method, researchers identified the factors causing the increase in the number of medical records for Covid-19 patients. The results obtained are based on attributes that have values, so the Bayesian value is 19.8714.
Co-Authors Friska Claudia Pasaribu Manusun Silitonga Yonata Laia