Prediction Of Customers at Bank Rakyat Indonesia  Using Backpropagation Algorithm

Pandu Nugroho

doi:10.59934/jaiea.v1i3.95

Authors

Pandu Nugroho STIKOM Tunas Bangsa

DOI:

https://doi.org/10.59934/jaiea.v1i3.95

Keywords:

Customer, Prediction, Algorithm, Backpropagation

Abstract

This study aims to see the development of the number of BRI bank customers in the following year. With this prediction, it is hoped that it can help bank bri in making policies related to customers who save more easily. The data source is obtained from Bank Rakyat Indonesia (BRI). In this study, researchers used the Backpropagation Algorithm. Backpropagation Algorithm is an algorithm that functions to reduce the error rate by adjusting the weight based on the desired output and target. The benefit of this research is to determine the increase or decrease in savings customers at the BRI bank in the following year. And artificial neural networks using the backpropogation algorithm can be applied in analyzing the increase in the number of bank bri customers by determining the best architectural model from a series of training and testing processes carried out.

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