Forecasting Passenger Numbers at Sri Bintan Pura Tanjungpinang Harbor: An Application of Double Exponential Smoothing

Dwi Rosida

Abstract

The maritime transportation sector is vital for managing the movement of people and goods, especially in coastal and island regions. Accurate passenger forecasting is essential for optimizing port operations and enhancing service delivery. This study applies Double Exponential Smoothing (DES) method to forecast passenger numbers at Sri Bintan Pura Tanjungpinang Harbor in Riau Islands Province. This method, known for its effectiveness in capturing trends and seasonality, has been utilized to predict passenger volumes based on historical data from 2015 to 2023 in this research. Secondary data were sourced from the Central Statistics Agency (BPS) of Riau Islands Province, encompassing domestic and international passenger statistics. Results indicate that DES provides highly accurate forecasts for domestic passengers, with Mean Absolute Percentage Errors (MAPE) of 4.53% for departures and 5.10% for arrivals, and good accuracy for international passengers, with MAPE values of 14.68% for departures and 16.14% for arrivals. Forecasts for 2034 suggest a significant increase in passenger numbers, with domestic departures reaching 1,430,393 and arrivals reaching 1,564,647, while international departures are projected reaching 747,056 and arrivals reaching 768,125. These projections highlight a substantial growth trajectory, emphasizing the need for strategic infrastructure development at the port. Recommendations include optimizing existing facilities, expanding terminal buildings, and enhancing transport infrastructure to accommodate forecasted increase. This study contributes to the literature by demonstrating the application of DES in maritime contexts, offering valuable insights for port management and regional planning.

Keywords

Double Exponential Smoothing (DES); maritime transportation; passenger forecasting

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References

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DOI: https://doi.org/10.20961/desa-kota.v8i1.92729.%25p

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