Weather Factor Analysis on Badminton Playing Decisions Using Naive Bayes Algorithm
Keywords:
Naive Bayes, Badminton, RapidMinerAbstract
By utilizing the Naive Bayes algorithm as a classification method, this study investigates how weather factors influence a person's decision to play badminton. The Badminton dataset, including attributes such as weather conditions, air temperature, humidity levels, and wind conditions, was collected and processed using RapidMiner software. The preprocessing stage involved data cleaning and transforming the attributes to be suitable for analysis. To predict the decision to play badminton based on weather conditions, the Naive Bayes algorithm was chosen due to its capability to compute class probabilities easily and effectively.This study found that weather factors significantly influence a player's decision to play badminton, and the Naive Bayes model demonstrated the ability to make reasonably accurate predictions. In conclusion, the Naive Bayes algorithm can be effectively used to predict players' decisions in playing badminton
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Copyright (c) 2025 Gusti Alfian, Ageng Samudro Ndiko Laksono, Ardiansyah, Mahis Duhan, Raffa Nurprasetyo Araya, Maulana Fansyuri (Author)
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