Sales Forecasting Analysis of Minyakita using POM-QM Application (Case Study: PT. Java Agri Sukses Makmur) - Zahara, Ardelia Fatimah As; Angelina, Vita; Nurfiyanti, Widia Putri; Miharin, Yatika; Salsabilla, Novy; Zulfa, Irma Indana; Sholikhah, Riadhu; Tondang, Ika Sari (Asia Pacific Network for Sustainable Agriculture, Food and Energy (SAFE-Network), 2025)
This observation analyzes Minyakita sales forecasting at PT Java Agri Sukses Makmur using the POM-QM application. Accurate sales forecasting is important for stock planning and management. Sales data were collected through interviews conducted over three months (March-May 2025). Three forecasting methods were employed, namely linear trend analysis, Single Exponential Smoothing, and Simple Moving Average. The results of Trend Analysis Linear show a sales pattern that tends to increase. The regression equation is Demand(y) = 11,267.68 + 881.664xTime. Although the Bias value (0.001) is close to zero, error values such as MAD (4,663,778), MSE (28,397,000), and Standard Error (5,837.5) show a fairly high error rate. However, the MAPE value (30.745%) is considered feasible for medium-term forecasting. The correlation coefficient of 0.496 and R² of 0.246 indicate a moderate relationship, with the variation in sales explained by time accounting for only 24.6%. Single Exponential Smoothing (α=0.1) resulted in a Bias of 1,684.15 (tends to underestimate) and MAPE of 32.77%, with a forecast of 17,307.56 units for the next period. Simple Moving Average shows a MAPE of 27.191% (feasible), with a forecast of 19,616.25 cartons. Overall, the linear trend model is suitable for identifying long-term patterns, but less responsive to short-term fluctuations. These forecasting results are expected to support PT Java Agri Sukses Makmur in production and marketing strategies. Contribution to Sustainable Development Goals (SDGs):SDG 2: Zero HungerSDG 8: Decent Work and Economic GrowthSDG 9: Industry, Innovation, and InfrastructureSDG 12: Responsible Consumption and Production