The Best Model for Predicting Tourists to Visit Kalibiru Tourism Object

DOI

10.2991/aebmr.k.200626.045How to use a DOI?

Keywords

ARIMA, GARCH, visitors, tourists, travelers

Abstract

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.

Copyright

© 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/).

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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  -