Foreign Tourists Arrival Forecasting at Major Airports in Indonesia: a Comparison of Holt-Winters and Exponential Smoothing Maximum Likelihood
Article Sidebar
Main Article Content
Abstract
Purpose: This research purports to forecast the number of foreign tourists arriving at major airport in Indonesia. The airports chosen are Soekarno Hatta, Juanda, I Gusti Ngurah Rai, and Kualanamu international airports.
Design/methodology/approach: The data used were foreign tourists arrival at major airports located in Jakarta, Surabaya, Medan, and Denpasar. The data extended from January 2014 until December 2018. Two time-series methods were employed, namely Holt-Winter Seasonality and Exponential Smoothing with maximum likelihood. The forecasts would reveal the fitted numbers of foreign tourists arriving from January 2019 until December 2019. The fitted numbers would then be compared to the actual numbers of January 2019 to December 2019.
Findings: The results showed that, overall, Holt-Winters seasonality excel at forecasting foreign tourists arrival at Soekarno Hatta and Juanda international airports. While Exponential Smoothing perform better for prediction at I Gusti Ngurah Rai and Kualanamu international airports. The MAPE for Holt-Winters at Soekarno Hatta and Juanda international airports were 26.1585% and 14.538%. The MAPE for Exponential Smoothing at at I Gusti Ngurah Rai and Kualanamu international airports were 7.76% and 15.6791%.
Research limitations/implications: Forecasting for foreign tourist arrival at Soekarno Hatta and Juanda international airports should employ Holt-Winters approach. Forecasting for foreign tourists arrival at I Gusti Ngurah Rai and Kualanamu international airports should employ Exponential Smoothing with maximum likelihood.
Practical implications: Certain forecasting methods work better than the others at certain international airports. Many forercasting methods are available. Two methods are specifically prominent for detecting seasonality and trend, i.e Holt-Winters and Exponential Smoothing with maximum likelihood.
Originality/value: Most research focus on one method at a time. This research compares two methods so that we can know better which method is suitable for certain airports. Four international airports are sampled in this study. Not many research focus on several places at a time.
Paper type: Research paper
Downloads
Article Details
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
References
Ardra, U., & Martawardaya, B. (2017). Tourism and Economic Development in ASEAN 1998-2013. Economics and FInance in Indonesia, 63(2), 114–125. https://doi.org/http://dx.doi.org/10.47291/efi.v63i2.571
Aryati, A., Purnamasari, I., & Nasution, Y. N. (2021). Peramalan Dengan Menggunakan Metode Holt-Winters Exponential Smoothing. EKSPONENSIAL, 11(1), 99–106.
Dewi, N. P., & Listiowarni, I. (2020). Implementasi Holt-Winters Exponential Smoothing Untuk Peramalan Harga Bahan Pangan di Kabupaten Pamekasan. Digital Zone: Jurnal Teknologi Informasi Dan Komunikasi, 11(2), 219–231. https://doi.org/https://doi.org/10.31849/digitalzone.v11i2.4797
Fauzi, N. F., Ahmadi, N. S., Shafii, N. H., & Halim, H. Z. (2020). A Comparison Study on Fuzzy Time Series and Holt-Winter Model in Forecasting Tourist Arrival in Lankawi, Kedah. Journal of Computing Research and Innovation, 5(1), 34–43. https://doi.org/https://doi.org/10.24191/jcrinn.v5i1.138
Hyndman, R. J., & Athanasopoulos, G. (2018). Forecasting: Principles and Practice (2nd. vyd.). Melbourne, Australia: OText. Dostupné na Internete. http://www.otexts.com/fpp2
Muna, S., & Kuntoro, K. (2021). Application of the Holt-Winters Exponential Smoothing Method on the Air Pollution Standard Index in Surabaya. Jurnal Biometrika Dan Kependudukan, 10(1), 53–60. https://doi.org/http://dx.doi.org/10.20473/jbk.v10i1.2021.53-60
Nurhamidah, Nusyirwan, & Faisol, A. (2020). Forecasting Seasonal Time Series Data Using The Holt-Winters Exponential Smoothing Method of Additive Models. Jurnal Matematika Integratif, 16(2), 151–157. https://doi.org/198/jmi.v16.n2.29293.151-157
Pertiwi, D. D. (2020). Applied Exponential SMoothing Holt-Winter Method for Rainfall Forecast in Mataram City. Journal of Intellegent Computing and Health Informatics, 1(2), 46–49.
https://doi.org/https://doi.org/10.26714/jichi.v1i2.6330
Primandari, A. H. (2017). An ALternative Forecasting Using Holt-Winter Damped Trend for Soekarno-Hatta Airport Passenger Volume. Eksakta. Journal of Sciences and Data Analysis, 17(1), 1–10. https://doi.org/https://doi.org/10.20885/eksakta.vol17.iss1.art1
Sujai, M. (2016). Strategi Pemerintah Indonesia Dalam Menarik Kunjungan Turis Mancanegara. Kajian Ekonomi & Keuangan, 20(1), 61–76. https://doi.org/https://doi.org/10.31685/kek.v20i1