MODELING AND FORECASTING THE TOTAL VOLUME OF GOODS TRANSPORTED BY RAIL IN INDONESIA USING SEASONAL AUTOREGRESSIVE INTEGRATED MOVING AVERAGE (SARIMA)

DOI: https://doi.org/10.30598/barekengvol19iss2pp829-842
Keywords: Forecasting, MAPE, Seasonal Autoregressive Integrated Moving Average, Train

Abstract

Transportation has an important role in supporting the mobility of people in Indonesia. Trains are included in the most widely used transportation category because they are effective and efficient, not only transporting passengers, trains also have a role in the distribution of goods. This study aims to model and forecast total volume of goods transported through rail transportation in Indonesia using the Seasonal Autoregressive Integrated Moving Average (SARIMA) Method because the data has seasonal trend. The data used comes from the Central Statistics Agency (BPS) from January 2013 to April 2024. The results were obtained that the SARIMA (0,1,1)(0,1,1)12  model is the best model with a MAPE value of 0.96% which is included in the category of accurate model. In addition to being an additional insight, this research can also be a reference in the management of railway transportation considering the number of uses both passengers, the distribution of goods that continue to increase, and can be recommendation for other research that same topic with it.

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Published
2025-04-01
How to Cite
[1]
I. Syahzaqi, S. Sediono, A. C. Anggakusuma, E. E. Wieldyanisa, and S. S. Oktavia, “MODELING AND FORECASTING THE TOTAL VOLUME OF GOODS TRANSPORTED BY RAIL IN INDONESIA USING SEASONAL AUTOREGRESSIVE INTEGRATED MOVING AVERAGE (SARIMA)”, BAREKENG: J. Math. & App., vol. 19, no. 2, pp. 829-842, Apr. 2025.
Issue
Vol 19 No 2 (2025): BAREKENG: Journal of Mathematics and Its Application
Section
Articles

Copyright (c) 2025 Idrus Syahzaqi, Sediono Sediono, Aurellia Calista Anggakusuma, Ezha Easyfa Wieldyanisa, Sabrina Salsa Oktavia

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