Proceedings of the 8th International Conference on Entrepreneurship and Business Management (ICEBM 2019) UNTAR

The Best Model for Predicting Tourists to Visit Kalibiru Tourism Object

Authors
Nuryasman M. N., Kartika Nuringsih
Corresponding Author
Nuryasman M. N.
Available Online 29 June 2020.
DOI
https://doi.org/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.
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Proceedings
8th International Conference of Entrepreneurship and Business Management Untar (ICEBM 2019)
Part of series
Advances in Economics, Business and Management Research
Publication Date
29 June 2020
ISBN
978-94-6252-980-9
ISSN
2352-5428
DOI
https://doi.org/10.2991/aebmr.k.200626.045How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

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  - 8th International Conference of Entrepreneurship and Business Management Untar (ICEBM 2019)
PB  - Atlantis Press
SP  - 255
EP  - 260
SN  - 2352-5428
UR  - https://doi.org/10.2991/aebmr.k.200626.045
DO  - https://doi.org/10.2991/aebmr.k.200626.045
ID  - M.N.2020
ER  -