Forecasting Model of Corn Commodity Productivity in Indonesia: Production and Operations Management, Quantitative Method (POM-QM) Software

Food is an essential ingredient needed by humans. In addition to being consumed, it can also be a valuable commodity for economic purposes through productivity of food crops. Therefore, this study aims model the forecasting maize in Indonesia using Production and Operations Management-Quantitative Method (POM-QM) software. The data collected on corn commodities between 1980-2019 shows fluctuations, with both deficit surplus periods. This uses time series data-based consisting three methods, namely Double Moving Average (DMA), Weighted (WMA), Single Exponential Smoothing (SES). selection best was conducted based Mean Absolute Deviation (MAD), Square Error (MSE), Percent (MAPE). SES emerged as most preferred, lower MAPE value 4.913%. predicted estimated at 5.28 tons/ha/year, sufficient meet consumers' demand. governments are recommended use information predicting national demand future.