Forecasting the Number of Foreign Tourist Visits to Indonesia Used Intervention Analysis with Step Function

Authors

  • Adelia Ramadhani Universitas Mulawarman
  • Sri Wahyuningsih Universitas Mulawarman
  • Meiliyani Siringoringo Universitas Mulawarman

DOI:

https://doi.org/10.20956/j.v19i1.21607

Keywords:

ARIMA, Foreign Tourists, Intervention Analysis, Step Function

Abstract

   Intervention analysis is a method for processing time series data that can be used to explain the effect of an intervention that is influenced by external and internal factors. One application of this method is the data on the number of foreign tourist visits. Since the emergence of COVID-19 in Indonesia, especially in March 2020, Indonesia has begun to implement a lockdown policy and restrict foreign tourists from entering Indonesia. Lockdown policy caused the number of foreign tourist arrivals to decreased drastically. The purpose of this study was obtained a model and forecast results for the number of foreign tourist arrivals for the period November 2021 to November 2022 used a step function intervention analysis. The results of the analysis was shown that the ARIMA intervention model (0,1,1) with a step function with an intervention orde of b=0, s=0, and r=0 was the best model. The results of forecasting the number of foreign tourist visits to Indonesia will increase slowly from November 2021 to November 2022 with a MAPE value 9.91%.

References

Aswi & Sukarna, 2006. Analisis Deret Waktu Aplikasi dan Teori. Makassar: Andira Publisher.

BPS. 2021. Statistik Kunjungan Wisatawan Mancanegara Tahun 2020. Indonesia: Badan Pusat Statistik.

Ekayanti, R., Mara, M. N., & Sulistianingsih, E., 2014. Analisis Model Intervensi Fungsi Step untuk Peramalan Kenaikan Tarif Dasar Listrik (TDL) Terhadap Besarnya Pemakaian Listrik. Buletin Ilmiah Mat., Stat., dan Terapannya (Bimaster), 3(3), 175-184.

Husnita, F., Wahyuningsih, S., dan Nohe, D. A., 2015. Analisis Spektral dan Model ARIMA untuk Peramalan Jumlah Wisatawan di Dunia Fantasi Taman Impian Jaya Ancol. Jurnal Eksponensial, 6(1), 21-29.

Kim, M.J., Lee, C., James, F., Petrick., Kim, Y.S. 2020. The Influence or perceivied risk and intervention on international tourists bevahiour during the Hong Kong protest: Aplication of an extended model of goal directed behaviour. Journal of Hospitality and Tourism Management. 45 (2020), 622-632.

Lingyu, T., Jun, W., Chunyu, Z., 2020. Mode Decomposition Method Integrating Mode Reconstruction, Feature Extraction, and ELM for Tourist Arrival Forecasting. Chhaos, Solitons & Frcatals. 143(2021).

Makridakis, S., Wheelwright, S.C., & McGree, V.E., 1999. Metode dan Aplikasi Peramalan (edisi ke-2). Jakarta: Erlangga.

Montgomery, D. C., Jenning, C.L., & Kulachi, M., 2008. Introduction to Time Series Analysis and Forecasting. New Jersey: John Wiley and Sons.

Salamah, M., Suhartono & Wulandari, S.P. 2003. Buku Ajar Analisis Time Series. Surabaya: Institut Teknologi Sepuluh Nopember.

Sari, R.N., Mariani, S., & Hendikawati, P., 2016. Analisis Intervensi Fungsi Step Pada Harga Saham (Studi Kasus Saham PT Fast Food Indonesia Tbk). UNNES Journal of Mathematics, 5(2), 181-189.

Suhartono., 2007. Teori dan Aplikasi Model Intervensi Fungsi Pulse. Jurnal Ilmiah MatStat: 7(2), 191-241.

Wei, W. S., 2006. Time Series Analysis: Univariate and Multivariate Methods (2nd Edition). New York: Addison Wesley Publishing Company.

Zhang, H., Song, H., Wen, L., Liu, C., 2021. Forecasting Tourism Recovery Amid COVID-19. Annals of Tourism Research. 87 (2021), 1-16.

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Published

2022-09-07

How to Cite

Ramadhani, A., Wahyuningsih, S. ., & Siringoringo, M. . (2022). Forecasting the Number of Foreign Tourist Visits to Indonesia Used Intervention Analysis with Step Function. Jurnal Matematika, Statistika Dan Komputasi, 19(1), 146–162. https://doi.org/10.20956/j.v19i1.21607

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Section

Research Articles