Transportation is vital for daily activities, including the movement of goods, services, and labor. In Indonesia, rail transport has been important since 1864, with Kereta Api Indonesia (Persero) providing services that help reduce congestion. Trains efficiently carry large volumes of goods at relatively low costs and with high time efficiency, making them crucial for economic growth.
In recent decades, rail freight volumes have risen significantly, growing by 7.87% to 5.7 million tons according to BPS data. This highlights the railway’s role in supporting mobility and goods distribution nationwide. To optimize logistics, accurate forecasting of transported goods is essential for scheduling, fleet management, and infrastructure planning.
The SARIMA method is effective for forecasting because it accounts for seasonal patterns, such as increases during harvest or holidays. While many studies have focused on passenger volumes, fewer have modeled freight. A prior study, “Forecasting the Number of Goods Through Rail Transportation in Indonesia Using SARIMA”, showed SARIMA’s accuracy with a lower MAPE value compared to earlier models.
This study aims to model and forecast the monthly volume of goods transported by rail in Indonesia using the Seasonal Autoregressive Integrated Moving Average (SARIMA) method. The data, sourced from the Central Statistics Agency (BPS), spans from January 2013 to April 2024 and shows a clear seasonal trend. After performing data transformations and differencing to achieve stationarity, the SARIMA (0,1,1)(0,1,1)12 model was selected as the best model, with a Mean Absolute Percentage Error (MAPE) of 0.96%, indicating excellent accuracy. This model effectively captures both trend and seasonality in the data. The forecasting results can be used to support decision-making in railway logistics, such as scheduling and capacity planning, and contribute to infrastructure development. Overall, the research supports the use of data-driven approaches to improve efficiency and sustainability in Indonesia’s rail freight transportation system.
Author: Idrus Syahzaqi, S.Stat., M.Stat
Details of the research can be viewed on: https://scholar.unair.ac.id/en/publications/modeling-and-forecasting-the-total-volume-of-goods-transported-by
