Analysis of the Naïve Bayes Classifier Method in Classifying the Weather Conditions in Aceh Tamiang

  • Syafira D
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Abstract

Naive Bayes Classifier is a method that aims to predict future conditions. This method is a sub-part of classification algorithms. In this study, tests were tested out to predict weather conditions at a certain time. The results of the studies carried out on 4 weather conditions in 3 different cities in Indonesia using Naive Bayes Classifier method the accurate prediction accuracy is 92.1%, while using ARIMA (Autoregressive Integrated Moving Average) method the accuracy results obtained are 86.8 %. These results indicate that Naive Bayes Classifier has a greater percentage level of accuracy than ARIMA, which is 5.3%.

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APA

Syafira, D. (2024). Analysis of the Naïve Bayes Classifier Method in Classifying the Weather Conditions in Aceh Tamiang. Journal of Advanced Computer Knowledge and Algorithms, 1(2), 47–51. https://doi.org/10.29103/jacka.v1i2.15889

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