<![CDATA[The need for communication technology that can find out the customer's buying interest is something that isneeded by the company, the goal is that the company can obtain consideration regarding product sales andappropriately take a policy regarding pricing of a product, the amount of product supply and so on. The naïvebayes classifier method is sufficient to be able to find out how much the customer's buying interest in aninternet package product is by analyzing the results of past sales, meaning that the Naive Bayes algorithmcan predict future opportunities based on past experience, by defining each class from all attribute. The naivebayes classification is assumed that there is or not a certain feature and a class has nothing to do with othercharacteristics and classes. This study defines several characteristics, namely operator, quota, active periodand product price. From the results of this study is the author can find the value of accuracy from the resultsof calculating interest and not by comparing the results of predictions with actual results outside the trainingdata. Based on data on internet package product sales as training data, the Naive Bayes method successfullyclassifies 10 product data with 858 transaction data as training data and 10 product data with 115 transactiondata as test data. From the analysis of all test data and training data, the truth ratio is 8/10, which is 8 out of10 products with predictive values that are of true value. So that the accuracy value is 80% and to find outthe customer's buying interest by calculating the sales data that has been past with the provisions and inaccordance with the specified label, the results of this prediction are expected to be a better policyconsideration for the sales business.Keywords: naïve bayes classifier, sales of internet package products.]]>
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