Control of Notebook Inventory Using an Integrated ABC, EOQ, and ROP Approach for Seasonal Demand Planning in the 2026 Academic Year at PT Senyum Media Utama - Johannata, Dimas; Muhsyi, Abdul; Handriyono; Noviasari, Tria Putri (Ilomata International Journal of Management, 2026)
This study aims to analyze and optimize notebook inventory control at PT Senyum Media Utama in order to anticipate the demand surge during the 2026 new academic year period (May–August). The current inventory policy relies heavily on experience-based decisions, which may result in overstock or stock shortages during seasonal fluctuations. Therefore, this research proposes a more systematic and quantitative approach by integrating ABC analysis, Economic Order Quantity (EOQ), Safety Stock, and Reorder Point (ROP). Inventory performance is evaluated based on total inventory cost efficiency and the establishment of quantitative reorder thresholds under a specified service level. Demand forecasting is conducted using monthly historical data from 2022 to 2024, with model validation through a train-test split approach. The results show that 9 Category A notebook products account for 70.02% of total annual inventory investment, highlighting their critical importance. Based on model assumptions, the EOQ method reduces projected total inventory costs from IDR 4,511,172 to IDR 3,664,004, resulting in an efficiency improvement of approximately 19%. In addition, Safety Stock and ROP calculations generate measurable reorder thresholds to support inventory availability and reduce stockout risk during peak demand, targeting a 95% service level. However, these findings are model-based and depend on assumptions such as constant holding costs, stable lead times, and the selected service level. Since the framework has not yet been implemented, further validation through real-world application or simulation is required. Future research is recommended to incorporate stochastic demand and lead time variability, as well as cross-company comparisons, to enhance the robustness and generalizability of the proposed approach.