Production Planning Forecasting using Seasonal and Non-Seasonal ARIMA Method with Minitab Applications (Study Case: DC Company) - Aulia Rahma Dieny; Timotius FCW Sutrisno (SAFE-Network, 2026)
This study aims to forecast the production of DMG (Mugs) and TM (Salt and Pepper Shakers) at DC Company, one of the leading ceramic producers in Malang City. Accurate forecasting is essential to support production planning, resource optimization, and market demand fulfillment, especially since the company’s primary market segment is wedding souvenirs with fluctuating demand. The research employs time series forecasting methods using ARIMA and SARIMA models, with historical production data from January 2021 to July 2025 as the dataset. Model identification, estimation, and verification were conducted using MINITAB 22, with performance evaluated through MSE, MAD, and MAPE values. The results show that the SARIMA (0,1,1)(1,1,1)₁₂ model provides the highest forecasting accuracy for both DMG and TM, outperforming ARIMA models. Forecasting results indicate a decline in DMG production for 2026, while TM production shows a relatively stable upward trend. These findings provide a practical basis for DC Company to develop production strategies, improve efficiency, and align marketing efforts with projected demand patterns.