Forecasting Tourist Visits Using Seasonal Autoregressive Integrated Moving Average Method

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Abstract

Bandung, a city in Indonesia is one of the favorite tourist destinations for foreign tourists. The purpose of this writing is predicted to the abundance of foreign tourists who come to Bandung city using the time series methods. Data the data used are foreign tourists entering through the Husein Sastranegara airport from the year 2010 to 2017. This research using Seasonal Autoregressive Integrated Moving Average Method in forecasting foreign tourists who come to the city of Bandung. Model accuracy was measured by comparing the percentage of the value of forecasting with the true value. This value is called the Mean Absolute Deviation (MAD). Based on the results of the comparison, the best value of SARIMA model MAD SARIMA model is the smallest (0, 1, 1) (1, 0, 0)12 with the value of the MAD 484,04. From the results it can be concluded that the model in the SARIMA model for forecasting made worth more.

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APA

Fahrudin, R. (2018). Forecasting Tourist Visits Using Seasonal Autoregressive Integrated Moving Average Method. In IOP Conference Series: Materials Science and Engineering (Vol. 407). Institute of Physics Publishing. https://doi.org/10.1088/1757-899X/407/1/012148

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