Forecasting of Rice Agricultural Production in Lamongan Regency Using the Brown's Double Exponential Smoothing Method
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Abstract
Rice production data from 14 sub-districts in Lamongan Regency during the 2008–2021 period, comprising 196 observations, exhibited variations over time. These fluctuations need to be anticipated because changes in rice production may affect rice availability. Therefore, a forecasting model is required to estimate rice production for the subsequent period as a basis for formulating agricultural and food security policies. The forecasting results can be utilized by the local government to plan rice reserve management, maintain price stability, optimize food distribution, and develop preventive measures in the event of a projected decline in production. This study applied the Brown Double Exponential Smoothing method to determine the smoothing parameter that produces the lowest forecasting error. Based on the evaluation of several alpha (α) values, α = 0.5 was identified as the optimal parameter, yielding the lowest Mean Absolute Percentage Error (MAPE) of 2.66%, indicating that the model has a relatively low forecasting error. Using this parameter, the forecasting model was obtained as: F_(t+m) = 791904.36 + 20071.34(m). The model was then used to forecast rice production in Lamongan Regency for 2022, resulting in an estimated production of 811,975.71 tons. In addition to evaluating the forecasting model, this study also assessed the developed system through questionnaire-based usability testing. The evaluation produced a feasibility score of 83.76%, which falls into the highly feasible category, indicating that the system is easy to learn, user-friendly, satisfying to use, and suitable for supporting decision-making in rice production planning.
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