Foreign Tourist Arrivals Forecasting Using Recurrent Neural Network Backpropagation through Time
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.
Author: Wayan Oger Vihikan
Journal Code: jptkomputergg170100
