Application of Data Mining Classification for Covid-19 Infected Status Using Algortima Naïve Method: Application of Data Mining Classification for Covid-19 Infected Status Using Algortima Naïve Method

Puji Hari Santoso (Universitas Nasional)
Fauziah Fauziah (Universitas Nasional)
Nurhayati Nurhayati (Universitas Nasional)

Jurnal Mantik
Vol. 4 No. 1 (2020): May: Manajemen, Teknologi Informatika dan Komunikasi (Mantik)

The number of virus infected status known as covid -19 is increasing in the southern Jakarta area, namely Pondok Labu, West Cilandak, Jagakarsa, Lenteng Agung, Pasar Minggu and Ragunan, it is necessary to classify the data to find out the negative status of covid-19 virus infection or positive infected with covid virus -19. The technique of classifying positive or negative covid-infected virus status with the naïve bayes classification method. To manage the data, software rapid miner 9. 6 is used, the infected status dataset covid -19 is obtained from the websitejeo. compass. CalculationPrediction shows the classification of the Naïve Bayes method obtained a positive prediction that shows a figure of 55.48% and a negative prediction result of 44.52%. From the results of the classification of data that has been obtained can be seen that the largest prediction found in the positive status infected with covid -19 virus reached 55.48%.