Peramalan Produksi Singkong Provinsi Lampung Indonesia dengan Metode Kuantitatif menggunakan Aplikasi POM QM - Radya Yogautami; Ulfah Izdihar; Elsa Windiastuti (Department of Agribusiness, Halu Oleo University Jointly with Perhimpunan Ekonomi Pertanian Indonesia - Indonesian Society of Agricultural Economics (PERHEPI/ISAE), 2025)
Cassava is considered a strategic commodity due to its versatility in processing into various products and its status as a significant source of carbohydrates, commonly consumed after rice and corn. Population growth indirectly increases overall consumption, leading to higher demand for cassava. To ensure this demand is met, maintaining a sufficient supply is essential. The objective of this study is to forecast cassava production trends in Lampung Province for 2025-2029 using data from 2019-2024. The forecasting process uses POM-QM for Windows Version 5 software and applies several forecasting methods, including Moving Average, Exponential Smoothing, Linear Regression, Weighted Moving Average, and Exponential Smoothing with Trend. These methods are evaluated using performance metrics including MAD (Mean Absolute Deviation), MAPE (Mean Absolute Percentage Error), and MSE (Mean Squared Error) to determine the most accurate approach. Among the tested methods, Exponential Smoothing with Trend was selected as the most suitable, supported by the regression equation y = 656.34x + 4435.5, which indicates strong predictive accuracy. Based on this model, cassava production is expected to continue increasing in the coming years, assuming expansion in planting areas and a higher Planting Index (PI). This projected growth presents opportunities for industries relying on cassava as a raw material and potentially opens the door to international market expansion. Using multi-method quantitative analysis in this study contributes to accurate data, more targeted agroindustrial policy strategies, and better business decisions.