Perfecting a Video Game with Game Metrics
Vol 15, No 3: September 2017

Foreign Tourist Arrivals Forecasting Using Recurrent Neural Network Backpropagation through Time

Wayan Oger Vihikan (Udayana University)
I Ketut Gede Darma Putra (Udayana University)
I Putu Arya Dharmaadi (Udayana University)



Article Info

Publish Date
01 Sep 2017

Abstract

Bali as an icon of tourism in Indonesia has been visited by many foreign tourists. Thus, Bali is one of the provinces that contribute huge foreign exchange for Indonesia. However, this potential could be threatened by the effectuation of the ASEAN Economic Community as it causes stricter competition among ASEAN countries including in tourism field. To resolve this issue, Balinese government need to forecast the arrival of foreign tourist to Bali in order to help them strategizing tourism plan. However, they do not have an appropriate method to do this. To overcome this problem, this study contributed a forecasting method using Recurrent Neural Network Backpropagation Through Time. We also compare this method with Single Moving Average method. The results showed that proposed method outperformed Single Moving Average in 10 countries tested with 80%, 70%, and 70% better MSE results for 1, 3 and 6 months ahead forecast respectively.

Copyrights © 2017






Journal Info

Abbrev

TELKOMNIKA

Publisher

Subject

Computer Science & IT

Description

Submitted papers are evaluated by anonymous referees by single blind peer review for contribution, originality, relevance, and presentation. The Editor shall inform you of the results of the review as soon as possible, hopefully in 10 weeks. Please notice that because of the great number of ...