Pemodelan dan prediksi jumlah penumpang pelabuhan bakauheni selama periode tsunami Selat Sunda menggunakan autoregressive integrated moving average

  • Dani Al Mahkya Program Studi Sains Aktuaria, Institut Teknologi Sumatera, Lampung Selatan, Indonesia 35365
  • Dian Anggraini Program Studi Sains Aktuaria, Institut Teknologi Sumatera, Lampung Selatan, Indonesia 35365
  • Andi Fitriawati Program Studi Sains Aktuaria, Institut Teknologi Sumatera, Lampung Selatan, Indonesia 35365
  • Radot MH Siahaan Program Studi Sains Aktuaria, Institut Teknologi Sumatera, Lampung Selatan, Indonesia 35365
DOI: https://doi.org/10.35472/jsat.v4i1.266

Abstract

Bakauheni Port is a ferry port located in Bakauheni District, South Lampung. This port is one of the major ports located on Sumatera island connecting Sumatera and Java and is located in the Sunda Strait. The tsunami that occurred in the Sunda Strait on December 22, 2018 indirectly affected the sea crossing node, especially the Bakauheni-Merak route. This can lead to changes in time series data patterns. The phenomenon is expected to be captured through a mathematical modeling that can be used as a decision making in the future. The purpose of this study was to model and predict the number of Bakauheni port passengers during the Sunda Strait Tsunami period using the Autoregressive Integrated Moving Average (ARIMA). The ARIMA approach uses past information as a basis for modeling. Based on visual information on the number of Bakauheni Port passengers, there was an increase in December in general. Other information is that there are seasonal patterns that occur with a span of 7 days. This was indicated by the pattern of repeated increases in the number of passengers every Sunday. After the tsunami, the number of passengers decreased for 2 days. In the 3 days after the Tsunami or during the Christmas holiday on December 25, 2018, the number of passengers has increased again. Based on the analysis and discussion that has been done, the best time series model obtained is ARIMA([5],1,2)(2,1,0)7 with a Mean Absolute Percentage Error (MAPE) of 9.55%.

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References

[1] Listantari, “Evaluasi Pelayanan Angkutan Lanjutan di Pelabuhan Penyeberangan Merak,” Jurnal Penelitian Transportasi Multimedia, vol. 14, pp. 84-94, 2016.
[2] Akmam, “Subduksi Lempeng Indo-Australia pada Lempeng Eurasia di Pantai Barat Sumatera Barat,” Jurnal Saintek, vol. 3, no. 1, pp. 52-59, 2011.
[3] S. M. Alif and A. Pratama, “Analysis of Southern Segment of Sumatran Fault Monitoring Bench Mark as Preliminary Approach in Updating Earthquake Hazard Map,” in Journal of Science and Applicative Technology in ICOSITER 2018, 2018.
[4] I. S. Sutawidjaja, “Pertumbuhan Gunung Api Anak Krakatau setelah Letusan Katastrofis 1883,” Jurnal Geologi Indonesia, vol. 1, no. 3, pp. 143-153, 2006.
[5] P. D. I. d. Humas, “BNPB (Badan Nasional Penanggulangan Bencana),” 14 02 2019. [Online]. Available: https://bnpb.go.id/berita/tsunami-selat-sunda. [Accessed 3 Juny 2020].
[6] X. Tang and G. Deng, “Prediction of Civil Aviation Passenger Transportation Based on ARIMA Model,” Open Journal of Statistics, vol. 6, pp. 824-834, 2016.
[7] S. W. Astuti and Jamaludin, “Forecasting Surabaya – Jakarta Train Passengers with SARIMA model,” IOP Conference Series, vol. 407, 2018.
[8] F. S. Gaya, Mbaga and Y. Vandi, “Modelling and Forecasting of Air Traffic Passengers of Yola International Airport,” Journal of Scientific and Engineering Research, vol. 5, pp. 155-161, 2019.
[9] W. W. S. Wei, Time Series Analysis Univariate and Multivariate Method, New York: Pearson Education, 2006.
[10] J. D. C. a. K. Chan, Time Series Analysis with Applications in R, Lowa City: Springer, 2008.
[11] D. C. Montgomery, C. Jennings and M. Kulachi, Introduction to Time Series Analysis and Forecasting, New Jersey: Willey, 2008.
[12] S. Makridakis, S. C. Wheelright and V. E. McGee, Metode dan Aplikasi Peramalan. Bahasa Indonesia, Jakarta: Erlangga, 1999.
Published
2020-06-15
How to Cite
MAHKYA, Dani Al et al. Pemodelan dan prediksi jumlah penumpang pelabuhan bakauheni selama periode tsunami Selat Sunda menggunakan autoregressive integrated moving average. Journal of Science and Applicative Technology, [S.l.], v. 4, n. 1, p. 32-37, june 2020. ISSN 2581-0545. Available at: <https://journal.itera.ac.id/index.php/jsat/article/view/266>. Date accessed: 19 apr. 2024. doi: https://doi.org/10.35472/jsat.v4i1.266.
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Vol 4 No 1 (2020): Journal of Science and Applicative Technology June Chapter
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