Prediksi Jumlah Kunjungan Wisatawan Mancanegara ke Indonesia

Aida Meimela

Abstract


Predict the number of foreign tourist's visit Indonesia.
In 2020 the Ministry of Tourism and Creative Economy has targeted the number of foreign tourists visiting Indonesia as many as 17 million visits. However, the number of foreign tourist visits decreased cumulatively (January- July 2020) by 64.64 per cent compared to the same period in 2019. Based on these conditions, it is significant to make accurate predictions to see if the target will be achieved or not in the future. One of the prediction methods used is Seasonal ARIMA (Autoregressive Integrated Moving Average). This model predicted the predictable number of foreign tourists visit in 2020 forecast to pass the target.

Keywords


Tourism; tourists; ARIMA; time series

References


Box, G. E. ., Jenkins, G. M., Reinsel, G. C., & Ljung, G. M. (2016). Time Series Analysis: Forecasting and Control (5th ed.). Jhon Wiley & Sons,Inc.

BPS. (2018). Statistik Kunjungan Wisatawan Mancanegara 2018. Badan Pusat Statistik RI.

BPS. (2020). Berita Resmi Statistik: Perkembangan Pariwisata dan Transportasi Nasional Juli 2020 (Issue 70/09/Th.XXIII).

Brida, J. G., & Garrido, N. (2011). Tourism Forecasting Using SARIMA Models in Chilean Regions. International Journal of Leisure and Tourism Marketing, 2(2), 176–190. https://doi.org/10.1504/ijltm.2011.038888

Chang, Y. W., & Liao, M. Y. (2010). A Aeasonal ARIMA model of Tourism Forecasting: The Case of Taiwan. Asia Pacific Journal of Tourism Research, 15(2), 215–221. https://doi.org/10.1080/10941661003630001

Iwok, I. A. (2017). Handling Seasonal Autoregressive Integrated Moving Average Model with Correlated Residuals. American Journal of Mathematics and Statistics, 7(June), 1–6. https://doi.org/10.5923/j.ajms.20170701.01

Kementerian PPN/Bappenas. (2019). Rancangan Teknokratik: Rencana Pembangunan Jangka Menengah Nasional 2020-2024. https://www.bappenas.go.id/id/berita-dan-siaran-pers/re/.

Kontan. (2020). Pemerintah Targetkan Sebanyak 17 Juta Wisatawan Mancanegara di Tahun 2020. https://nasional.kontan.co.id/news/pemerintah-targetkan-sebanyak-17-juta-wisatawan-mancanegara-di-tahun-2020.

Kumar, M., & Sharma, S. (2016). Forecasting Tourist In Flow In South East Asia: A Case of Singapore. Tourism and Management Studies, 12(1), 107–119. https://doi.org/https://doi.org/10.18089/tms.2016.12111

Lewis, C. D. B. G. S. (1982). Industrial and Business Forecasting Methods. Kent:Butterworths.

Makoni, T., & Chikobvu, D. (2018). Modelling and Forecasting Zimbabwe’s Tourist Arrivals Using Time Series Method: A Case Study of Victoria Falls Rainforest. Southern African Business Review, 22. https://doi.org/10.25159/1998-8125/3791

Mulyaningsih, T. (2015). Model Generalized Space Time Autoregressive Integrated untuk Peramalan Indeks Harga Konsumen Beberapa Kota di Jawa Tengah. Universitas Padjadjaran.

Razali, N. M., & Wah, Y. B. (2011). Power Comparisons of Shapiro-Wilk , Kolmogorov-Smirnov, Lilliefors and Anderson-Darling Tests. Journal of Statistical Modeling and Analytics, 2(1), 21–33. https://doi.org/doi:10.1515/bile-2015-0008

Wei, W. W. . (2005). Time Series Analysis Univariate and Multivariate Methods (2nd ed.). Pearson Education, Inc.Addison Wesley.

Zakaria, S., Al-Ansari, N., Knutsson, S., & Al-Badrany, T. (2012). ARIMA Models for weekly rainfall in the semi-arid Sinjar District at Iraq. Journal of Earth Sciences and Geotechnical Engineering, 2(3), 25–55.




DOI: https://doi.org/10.36276/mws.v19i1.376

Refbacks

  • There are currently no refbacks.


Copyright (c) 2020 Aida Meimela

Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.