The Best Model for Predicting Tourists to Visit Kalibiru Tourism Object
- 10.2991/aebmr.k.200626.045How to use a DOI?
- ARIMA, GARCH, visitors, tourists, travelers
Tourism sector is the most effective sector in encouraging an increase in Indonesia’s foreign exchange, although there is no forecasting model that can be used to predict the number of tourist visits. This study attempted to fill the void of the model to predict the number of tourist visits to Kalibiru in particular and to Indonesia in general. Based on the value of Root Mean Squared Error (RMSE) and forecasting ability measured by the value of Mean Absolute Percentage Error (MAPE), from the 4 proposed models, which were ARIMA, GARCH (0.2), GARCH (2.1) and GARCH (2.2), the GARCH model (2.1) was concluded as the best model to predict the number of tourist visits to Kalibiru tourism object.
- © 2020, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Nuryasman M. N. AU - Kartika Nuringsih PY - 2020 DA - 2020/06/29 TI - The Best Model for Predicting Tourists to Visit Kalibiru Tourism Object BT - Proceedings of the 8th International Conference on Entrepreneurship and Business Management (ICEBM 2019) UNTAR PB - Atlantis Press SP - 255 EP - 260 SN - 2352-5428 UR - https://doi.org/10.2991/aebmr.k.200626.045 DO - 10.2991/aebmr.k.200626.045 ID - M.N.2020 ER -