Classification Data for Direct Marketing using Deep Learning

Abstract

One of the tasks of banking marketing is to analyze customers' data and to find out the potential customers to save deposits. Generally, the method used to analyze customer data is by classifying all customers who have taken the time deposit into the target marketing, so this method causes the high cost of marketing operations. Therefore, this research is conducted to help solve the problem by designing a data mining application that can serve to classify the criteria of customers who potentially to save deposits in the bank. In classifying customer data has been done a lot by researchers before with various algorithms, now researchers use deep learning to classify the target in want by the banking. The results showed that achieved using deep learning accuracy is = 80%, MSE = 0.0943, AUC = 0.8533. The results of this study can be reference to build an application that can facilitate the banking in obtaining its target marketing in the future.