Using the Box-jenkins Autoregressive Integrated Moving Average Method in Cabbage Production Forecasting

Method Uses for Forecasting Cabbage Production

Abstract

The research objective was to predict cabbage (Brassica oleracea L.) production using Box- jenkins autoregressive integrated moving average (ARIMA) method. This method is suitable in time series data with observational values that are statistically related to one another. Cabbage is one of the main agricultural commodities in Batu city, with a productivity of 180 quintals per hectare in year 2022. Based on the economic potential of the cabbage crop which is quite high, forecasting the production of cabbage is necessary to optimize inventory management and supply planning. The data used on monthly cabbage yield in Batu for the last five years from January, 2018 to December, 2022 which is 60 observations as the basis for analysis. The analysis result shows that the best model for prediction cabbage production is ARIMA (1,0,0) and forecasting result for the next twelve months shows a constant pattern. The model produces a MAPE value of 6.09% means that the accuracy of the model is 93.91% so, it can be concluded that the model is suitable for use in the analysis of cabbage production data. The results of this study are expected to provide valuable insights for farmers, traders and other related parties in optimizing the production, distribution and marketing strategies of cabbage in Batu city.