Penerapan Model ARIMA dalam Peramalan Permintaan untuk Meningkatkan Efesiensi Manajemen Persediaan pada CV Kopi Biji Palembang - Gymnastiar, Muhammad; Anwar, Andries (Jurnal Teknik Industri Terintegrasi (JUTIN), 2025)
This study is motivated by unpredictable demand fluctuations at CV Kopi Biji Palembang, which often result in the risk of both overstock and stockout. The research aims to improve inventory management efficiency through the application of the ARIMA (Autoregressive Integrated Moving Average) model for coffee demand forecasting. This quantitative study utilizes six months of historical demand and inventory data, with steps including parameter identification (p,d,q), stationarity testing, and model evaluation using AIC, BIC, and MAPE. The results show that the ARIMA (1,1,1) model provides highly accurate predictions with a MAPE of 0.65%, effectively reducing overstock and stockout risks, lowering storage costs, and supporting more precise procurement planning. This study recommends integrating ARIMA forecasting results with EOQ and safety stock calculations to optimize inventory decision-making.