Forecasting The Number of Foreign Tourism Visits to Indonesia using Seasonal Autoregressive Integrated Moving Average (SARIMA) and Holt-Winters Approach

DOI

10.2991/978-94-6463-566-9_23How to use a DOI?

Keywords

Forecasting; Foreign Tourists; Economy; SARIMA; Holt-Winters

Abstract

The tourism sector is one of the economic sectors that shows the fastest growth rate and is the largest foreign exchange contributor in a large number of countries, including Indonesia. In the third quarter of 2023, Indonesia’s tourism sector generated more than USD 6 billion, which is equivalent to 3.76% of Indonesia’s GDP. Foreign tourists have high potential in supporting tourism stability and economic growth. With the target of foreign tourist visits for 2023 reaching 7.4 million, it is important to forecast the number of foreign tourism visits accurately. This study aims to analyze the prediction results of forecasting the number of foreign tourist visits to Indonesia for the period from January 2023 to December 2023. The data used is data on the number of foreign tourist visits to Indonesia for the period from January 2013 to December 2023. The methods used in this study are the Seasonal Autoregressive Integrated Moving Average (SARIMA) and Holt-Winters methods. The models generated in this study are SARIMA(1,1,0)(0,1,1)12 and Holt-Winters with parameters alpha 0.6, beta 0.1, and gamma 0.1. Based on the comparison of accuracy values, it is known that the SARIMA model has a better accuracy value than the Holt-Winters model. This is because the RMSE and AIC values of the SARIMA model are smaller than the Holt-Winters model, which are 113,504.54 and 313.17. Therefore, based on this research, the SARIMA method is a suitable method for forecasting the number of foreign tourist visits for the period January 2023 to December 2023.

Copyright

© 2024 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Indah Fahmiyah
AU  - Lidya Septi Andini
AU  - Mohammad Ghani
PY  - 2024
DA  - 2024/11/01
TI  - Forecasting The Number of Foreign Tourism Visits to Indonesia using Seasonal Autoregressive Integrated Moving Average (SARIMA) and Holt-Winters Approach
BT  - Proceedings of the  International Conference on Advanced Technology and Multidiscipline (ICATAM 2024)
PB  - Atlantis Press
SP  - 354
EP  - 371
SN  - 2352-5401
UR  - https://doi.org/10.2991/978-94-6463-566-9_23
DO  - 10.2991/978-94-6463-566-9_23
ID  - Fahmiyah2024
ER  -