A Classification of Customer Interests in Health Insurance Sales using the Naïve Bayes Classifier Method

Research on Classification of Customer Interest Data and Accuracy of the Naive Bayes Classifier Method

Abstract

In the banking world, there are products that are offered to customers, one of which is insurance, the insurance offered to customers is health insurance. Insurance companies store customer data, this data is very important for banking companies to find out the criteria for customers who are interested in the insurance they offer. With the existence of information from existing customer data, if the data is dug properly, patterns can be found for data mining with classification methods. Data mining is a technique that can help businesses find something very important from a set of data. By classifying using the Naive Bayes classifier algorithm, it is hoped that customer interest can be predicted by classifying customer data and experiments and analyzes are carried out to increase nave Bayes accuracy by applying the feature selection method.