Implementasi Algoritma Naive Bayes Untuk Mengetahui Minat Beli Konsumen Terhadap Sarang Burung Walet

Implementation of the Naive Bayes Algorithm to determine consumer buying interest in swallow nests. This study implements the Naive Bayes algorithm for managing data analysis which is used to classify new case data based on samples from training data by calculating the probability or probability value of each class. The number of samples used in this analysis is 25 training data records that are calculated manually or using the rapidminer application. The results of the calculation by applying the nave Bayes algorithm by multiplying the probability value or the probability value of the cases taken from the training data can be seen that P(X|Classification=”Interest”) gets greater results than P(X|Classification='No” ) with a value of interest = 0.233739 and a value of 0.00078. In addition, the results of data processing with the rapidminer application show that the new case data in the training data is included in the "Interest" classification category with the prediction results of interest with an interest confidence number of 0.983 with 24 consumers and 0.990 for 25 consumers with a comparison of confidence results not 0.017 and 0.010. So it can be concluded that the two new case data in the training data are included in the "Interest" classification category. This shows that the results of processing with the Naive Bayes algorithm are very accurate.