| dc.description.abstract | In the oil and gas industry, efficient and accurate management of LNG cargo loading and unloading is crucial to ensure the smooth operation of the terminal and optimal resource management. PT Perta Arun Gas is a terminal that functions to import liquefied natural gas (LNG), which is then converted into natural gas through the regasification process, and serves as a Hub for both Domestic and International LNG. This research aims to apply suitable forecasting methods to anticipate the demand for LNG cargo loading and unloading at the PT Perta Arun Gas Hub Terminal.Forecasting plays a significant role in assisting companies in addressing complex issues related to supply chain management, capacity allocation, and effective inventory management. This study focuses on the development and implementation of various forecasts tailored to the data patterns generated, along with inputting previous cargo loading and unloading demand data totaling 1,303,792 m³. Subsequently, actual historical data on cargo loading and unloading demands are used as the basis for forecasting, including the use of time series and trend analysis applied to project demand for the next 3 periods.The results of this study indicate that the SARIMA method is used for forecasting because this method accumulates the total error values and is consistent with the data pattern. After conducting the forecast, it is found that the demand for LNG in the next 3 periods experiences the same demand as the actual data, but the trend formed increases from the previous period. Thus, the company can manage terminal operations more efficiently by scheduling loading and unloading accurately, avoiding excess inventory that can lead to a decrease in demand and harm the company. Additionally, this optimization of terminal operations ensures better customer satisfaction by meeting their needs more effectively. | en_US |
