期刊名称：TELKOMNIKA (Telecommunication Computing Electronics and Control)
印刷版ISSN：2302-9293
出版年度：2017
卷号：15
期号：3
页码：1257-1264
DOI：10.12928/telkomnika.v15i3.5993
语种：English
出版社：Universitas Ahmad Dahlan
其他摘要：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.
关键词：Backpropagation Through Time;forecasting;tourism;Recurrent Neural Network
