Implementasi Algoritma Naive Bayes untuk Klasifikasi Pola Cuaca Berdasarkan Dataset di Stasiun Soekarno Hatta

This research explains how to use datasets from the Soekarno Hatta meteorological station to classify weather patterns using the Naive Bayes algorithm. The probability-based Naive Bayes algorithm was chosen for its ease of use and effectiveness in handling large and complex data sets. The dataset used in this research contains various meteorological factors collected over a certain period of time, including temperature, humidity, air pressure and wind speed. The research procedure requires pre-processing the data, separating it into training and test sets, and using the Naive Bayes algorithm to forecast the weather. The findings of this research show that the Naive Bayes algorithm can categorize weather patterns accurately to a sufficient level.