Classification of Determining Pancemic Status in Kupang City Using Naive Bayes Classifier Algorithm

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Nelci Dessy Rumlaklak
Adriana Fanggidae
Yulianto Triwahyuadi Polly

Abstract

The World Health Organization (WHO) made the corona virus a pandemic in 2020. This virus has hit the whole world, including Indonesia. East Nusa Tenggara (NTT) as of June 2021 recorded 18,741 positive cases of Covid-19 and the City of Kupang was the area that contributed the most positive cases. The daily increase in Covid-19 cases in Kupang City shows a fairly high increase. The purpose of this study is to build a classification system to determine the status of the Covid-19 zone in the city of Kupang. The system design using the waterfall model is used to design and build the system while the Naïve Bayes Classifier algorithm is used for classification. The criteria as input in the system for the classification process are positive confirmed data, recovered patient data and death data. The results of the classification process consist of 2 classes, namely the Green Zone and Red Zone. Kupang City's daily Covid-19 case data for January-June 2021 with a total of 181 as training data. 31 test data entered into the system were analysed using the Naïve Bayes Classifier method and succeeded in obtaining classification results as system output. Tests in the study were carried out on systems built using Blackbox testing to test the functionality of the system with the expected results. The confusion matrix is ​​used to test the performance of the classification method and the results have an accuracy rate of 77.91% and a precision value of 73.91%.

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How to Cite
[1]
N. Rumlaklak, A. Fanggidae, and Y. Polly, “Classification of Determining Pancemic Status in Kupang City Using Naive Bayes Classifier Algorithm”, jicon, vol. 10, no. 1, pp. 24-30, Mar. 2022.
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