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All Journal Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi)
Muhammad Ikbal
Program Studi Informatika, Fakultas Teknologi Komunikasi dan Informatika, Universitas Nasional
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management

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Visualisasi dan Analisa Data Penyebaran Covid-19 dengan Metode Klasifikasi Naïve Bayes Muhammad Ikbal; Septi Andryana; Ratih Titi Komala Sari
Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Vol 5 No 4 (2021): OCTOBER-DECEMBER 2021
Publisher : KITA Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jtik.v5i4.233

Abstract

The covid-19 virus became a pandemic in 2020. The spread of covid cases has hit the whole world, reaching 63 million cases in 190 countries as of November 2020. Information regarding the spread of covid is necessary for the general public. This research will produce a system that can provide information on the geographic distribution of covid cases. The data on the distribution of covid cases in this study were also used to analyze the classification using the Naive Bayes Classifier method. The Naive Bayes Classifier method works by using probability calculations so that this research can be used to classify the covid status in an area. The results of this study have succeeded in providing information on the status of the covid pandemic based on data on covid cases that have occurred around the world. Covid case data becomes training data for the analysis of the Naive Bayes classifier method so that it can determine the status of the Covid pandemic based on test data provided by system users. This research has succeeded in helping users to know the status of the Covid pandemic in an area well because it has reliable training data.
Co-Authors Ratih Titi Komala Sari Septi Andryana