Abstract
This study aims to determine the application of the naive bays method for classification in Weather datasets using the systematic literature review method. Weather forecasting research is an interesting object to study because weather is one of the things that influences everyday life so good accuracy in weather forecasts is very much needed. This study uses the systematic literature review method, which is a process of identifying, assessing, and interpreting facts and evidence from available research with the aim of finding answers to a particular research question. Climate change and weather are problems faced by almost the whole world which classify and predict. The problem is that there are many influencing variables, so it is quite difficult and unpredictable. Climate and weather change is human-caused global warming which makes it more difficult to solve weather problems. The results of this study can be used to measure the level of accuracy and MSE of the weather. the dataset serves as a metric for determining precipitation groups and it is concluded that the system can make predictions with an accuracy probability of up to 92% on new data. for the precision class to get a result of 100% where the system can predict the suitability of the class that is relevant to the results of the selected class.
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