E3S Web Conf.
Volume 328, 2021International Conference on Science and Technology (ICST 2021)
|Number of page(s)||5|
|Section||Information System, Big Data, Design Application, IOT|
|Published online||06 December 2021|
Application Of Naïve Bayes to Predict the Potential of Rain in Ternate City
Departmen Informatic, Faculty Engineering Khairun University, 97728 Ternate, Indonesia
* Corresponding author: email@example.com
The amount of rainfall that occurs cannot be determined with certainty, but it can be predicted or estimated. In predicting the potential for rain, data mining techniques can be used by classifying data using the naive Bayes method. Naïve Bayes algorithm is a classification method using probability and statistical methods. The purpose of this study is how to implement the naive Bayes method to predict the potential for rain in Ternate City, and be able to calculate the accuracy of the Naive Bayes method from system created. The highest calculation results with new data with a total of 400 training data and 30 test data, obtained 30 correct data with 100% precision, 100% recall and 100% accuracy and the lowest calculation results with new data with a total of 500 training data and 50 test data, obtained 38 correct data and 12 incorrect data with a percentage of precision 61.29%, recall 100% and accuracy 76%.
Key words: Naïve Bayes / Statistical Methods / Data Mining
© The Authors, published by EDP Sciences, 2021
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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