Forecasting Passengers Arriving and Departing at Sentani International Airport Terminal Using the ARIMA Method

Authors

  • Jemi Victor Palpialy Politeknik Penerbangan Jayapura
  • Rifqi Raza Bunahri Politeknik Penerbangan Jayapura https://orcid.org/0009-0006-9932-3839
  • Musri Kona Politeknik Penerbangan Jayapura
  • Dhian Supardam Politeknik Penerbangan Indonesia Curug
  • Hadi Prayitno Akademi Penerbang Indonesia Banyuwangi

DOI:

https://doi.org/10.31933/dijdbm.v4i6.2114

Keywords:

airplane passenger forecast, ARIMA model, sentani airport

Abstract

The airport terminal is one of the impacts of Covid-19 which can still be felt with a decrease in the number of arriving passengers and the number of departing passengers. The sentani international airport terminal adjusts airport activities along with normalization after covid-19. The purpose of this study was to determine the number of arriving passengers and the number of departing passengers at the Sentani International Airport terminal by forecasting using the ARIMA forecasting method. This research method uses the ARIMA method. The results show that the best model for forecasting the number of incoming passengers is the ARIMA (1.1.1) model with an RMSE value of 31433.34, MAE of 23993.72, and MAPE of 5207.000, and the number of departing passengers with the ARIMA (1.1.1) model with RMSE of 25220.27, MAE of 18720.95, and MAPE of 11690.43. The ARIMA model can provide accurate forecasts if conducted over a short or brief time frame.

References

Azaro, K., Riwajanti, N. I., & Kusmintarti, A. (2020). Triple Exponential Smoothing: Forecasting Perbandingan Penumpang Kereta Api Dan Pesawat Terbang. Media Mahardhika, 18(2), 277–286.
Bidang Statistik Distribusi. (2020). Statistik Transportasi Provinsi Papua Tahun 2019. Badan Pusat Statistik Provinsi Papua.
Bidang Statistik Distribusi. (2021). Statistik Transportasi Provinsi Papua Tahun 2020. Badan Pusat Statistik Provinsi Papua.
Bidang Statistik Distribusi. (2022). Statistik Transportasi Provinsi Papua Tahun 2021. Badan Pusat Statistik Provinsi Papua.
Dheviani, S., Wardono, W., & Hendikawati, P. (2018). Peramalan Banyaknya Penumpang Di Bandar Udara Internasional Ahmad Yani Semarang Dengan Mempertimbangkan Special Event. PRISMA, Prosiding Seminar Nasional Matematika, 1, 434–444.
Durrah, F. I., Yulia, Y., Parhusip, T. P., & Rusyana, A. (2018). Peramalan Jumlah Penumpang Pesawat Di Bandara Sultan Iskandar Muda Dengan Metode SARIMA (Seasonal Autoregressive Integrated Moving Average). Journal of Data Analysis, 1(1), 1–11.
Farida, Y., Yusi, S., & Yuliati, D. (2021). Peramalan Jumlah Penumpang Pesawat Di Bandar Udara Internasional Juanda Menggunakan Metode Exponential Smoothing Event-Based. BAREKENG: Jurnal Ilmu Matematika Dan Terapan, 15(4), 709–718. https://doi.org/10.30598/barekengvol15iss4pp709-718
George E. P. Box, G. M. J. (1976). Time Series Analysis: Forecasting and Control (1st Editio). Holden-Day.
Gischa, S. (2022). 5 Provinsi di Pulau Papua. Kompas.Com, 3. https://www.kompas.com/skola/read/2022/08/08/150000969/5-provinsi-di-pulau-papua?page=all.
Iqbalullah, J., & Winahju, W. S. (2014). Peramalan Jumlah Penumpang Pesawat Terbang di Pintu Kedatangan Bandar Udara Internasional Lombok dengan Metode ARIMA Box-Jenkins, ARIMAX, dan Regresi Time Series. Jurnal Sains Dan Seni ITS, 3(2), D212--D21.
Jannah, N. F., Fuady, M. B. I., & Prasetianto, S. (2017). Peramalan Jumlah Penumpang Bandara I Gusti Ngurah Rai Dengan Menggunakan Metode Autoregressive Integrated Moving Average (Arima). Prosiding Konferensi Nasional Penelitian Matematika Dan Pembelajarannya, 117–123.
Mujtaba, W. F., Srinadi, I. G. A. M., & Sumarjaya, I. W. (2021). Peramalan Jumlah Penumpang Pesawat Bandara I Gusti Ngurah Rai Menggunakan Exponential Smoothing Dan Ruey-Chyn Tsaur. E-Jurnal Mat, 10(4), 222.
Undang-Undang Republik Indonesi No 1 Tahun 2009 tentang Penerbangan, (2009).
SC, M. S. W., & McGee, V. E. (1999). Metode dan Aplikasi Peramalan (Jakarta: Binarupa Aksara). Binarupa Aksara.
Wei, W. W. S. (2006). Time series analysis: univariate and multivariate. In Methods. Boston, MA: Pearson Addison Wesley. Pearson Education.Inc.

Downloads

Published

2023-11-30

Issue

Vol. 4 No. 6 (2023): Dinasti International Journal of Digital Business Management (October-November 2023)

Section

Articles

License

Authors who publish their manuscripts in this journal agree to the following conditions:

  1. The copyright on each article belongs to the author(s).
  2. The author acknowledges that the Dinasti International Journal of Digital Business Management (DIJDBM) has the right to be the first to publish with a Creative Commons Attribution 4.0 International license (Attribution 4.0 International (CC BY 4.0).
  3. Authors can submit articles separately, arrange for the non-exclusive distribution of manuscripts that have been published in this journal into other versions (e.g., sent to the author's institutional repository, publication into books, etc.), by acknowledging that the manuscript has been published for the first time in the Dinasti International Journal of Digital Business Management (DIJDBM).