Comparison of Moving Average and Double Exponential Smoothing Methods in Rice Production Forecasting Based on NTB Satu Data
DOI:
https://doi.org/10.32493/sm.v8i1.52806Keywords:
Forecasting, Moving Average, Double Exponential Smoothing, Rice Production, NTB Satu DataAbstract
The rapid development of technology in the industry 4.0 era has led to the emergence of the data literacy era, where data is no longer merely supporting information but has become a strategic asset in decision-making. Recognizing the importance of data utilization, the West Nusa Tenggara/Nusa Tenggara Barat (NTB) Provincial Government launched the NTB Satu Data program through Governor Regulation No. 45 of 2021. This program provides an open, standardized, and integrated sectoral data platform managed by the NTB Communication, Information, and Statistics Agency. Through this platform, data is collected, validated, analyzed, and visualized so that it can be utilized for evidence-based policy planning. This study utilizes annual rice production data from 2001 to 2024 from the NTB Satu Data portal to forecast rice production in 2025. Two commonly used time series forecasting methods, Moving Average (MA) and Double Exponential Smoothing (DES), are applied and compared in terms of accuracy. Evaluation was conducted using the Mean Absolute Percentage Error (MAPE) and Mean Absolute Deviation (MAD) metrics. The analysis results show that the DES (Holt) method produced a MAPE of 9.455% and a MAD of 158.533, outperforming the MA order 2 method with a MAPE of 9.746% and a MAD of 161.700. These findings indicate that DES is more adaptive in capturing historical trend patterns and more effective in modeling production changes over time. The results of this study are expected to provide input for local governments in designing food security policies that are responsive to production dynamics. Utilizing these forecasts will enable more appropriate allocation of resources, increased preparedness for potential food supply disruptions, and strengthening of sustainable food security in NTB Province.
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