Penerapan Data Mining Untuk Peminatan Rasa Roti Bakar Di CV. Sariraos Menggunakan Metode Naïve Bayes

Abstract

Changes in buyer behavior towards the times this causes culinary business actors to innovate so that businesses continue to run and survive this will have a major effect on the income and turnover obtained to develop a taste interest in CV Sariraos toast by analyzing data mining and its use of naïve Bayes methods. To calculate the odds of one class and each attribute and determine which class is the most optimal, then the analysis is explained using the rapidminer application, its usefulness is to predict accuracy data and using the naïve Bayes method is expected to provide accurate decisions in determining recommendation of taste interest, classification method and predictions that represent these rules are then developed by calculating the confusion matrix formula based on the results of the research, so it can be concluded that with the naïve Bayes method, the most preferred taste is chocolate by testing using an applica. the rapidminer shows the accuracy rate obtained is 92.64%.

Keywords: taste interest, data mining, Naïve Bayes, Rapidminer, Confusion matrix