Journal of Information Technology and Computer Science
Vol. 6 No. 2: August 2021

Website Visitors Forecasting using Recurrent Neural Network Method

Arya, Putu Bagus (Unknown)
Firdaus Mahmudy, Wayan (Unknown)
Basuki, Achmad (Unknown)



Article Info

Publish Date
03 Sep 2021

Abstract

Abstract. The number of visitors and content accessed by users on a site shows the performance of the site. Therefore, forecasting needs to be done to find out how many users a website will come. This study applies the Long Short Term Memory method which is a development of the Recurrent Neural Network method. Long Short Term Memory has the advantage that there is an architecture of remembering and forgetting the output to be processed back into the input. In addition, the ability of another Long Short Term Memory is to be able to maintain errors that occur when doing backpropagation so that it does not allow errors to increase. The comparison method used in this study is Backpropagation. Neural Network method that is often used in various fields. The testing using new visitor data and first time visitors from 2018 to 2019 with vulnerable time per month. The computational experiment prove that the Long Short Term Memory produces better result in term of the mean square error (MSE) comparable to those achieved by Backpropagation Neural Network method.

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Journal Info

Abbrev

jitecs

Publisher

Subject

Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering

Description

The Journal of Information Technology and Computer Science (JITeCS) is a peer-reviewed open access journal published by Faculty of Computer Science, Universitas Brawijaya (UB), Indonesia. The journal is an archival journal serving the scientist and engineer involved in all aspects of information ...