Procurement Planning of Coffee Bean at Small Scale Agro-Industry in Kalibaru Banyuwangi Regency

Abstract Procurement planning with forecasting techniques is constructive for the agro-industry in dealing with price fluctuations and uncertainty in the availability of quality raw materials and controlling procurement costs. However, not all agro-industries can implement procurement planning accurately and precisely because it is unsuitable for the data characteristics and limited data. This study aims to forecast the amount of raw material needed for KUB Srikandi in the future using the ARIMA Model. The results of the study show that there are two models in the ARIMA family: ARIMA (1,1,0) and ARIMA (0,1,1), both of which have significant parameters with p-values below 0.05. But the ARIMA (0,1,1) model is the best model, according to the results of the model with the lowest Mean Squared Error (MSE) value among all the models that were looked at. The purchase planning quantitative analysis results are 191 kg/month at the lower limit and 213 kg/month at the upper limit.