Optimizing Raw Material Inventory Efficiency in Small-Scale Agroindustry Using the Economic Order Quantity Model: Evidence from a Milkfish Floss Enterprise in Indonesia

Abstract

Background: Efficient raw material inventory management is essential for maintaining production continuity and minimizing operational costs in small-scale agroindustries. Many micro and small enterprises still rely on conventional purchasing practices without systematic inventory planning, which often leads to overstocking, stock shortages, and increased storage costs. In the fish processing sector, particularly in milkfish floss production, the perishable nature of raw materials further increases the importance of accurate inventory control. The application of quantitative inventory models such as the Economic Order Quantity (EOQ) approach can provide a structured framework to determine optimal ordering decisions and improve operational efficiency in small agroindustrial enterprises.

Aims: This study aims to analyze raw material inventory control in a small-scale milkfish floss enterprise and evaluate the effectiveness of the Economic Order Quantity (EOQ) model in determining optimal order quantity, reorder point, safety stock, and total inventory cost.

Methods: A quantitative case study approach was applied using operational data collected from January to December 2024 at a milkfish floss enterprise located in Situbondo, Indonesia. The analysis utilized the EOQ model to calculate optimal order quantity, ordering frequency, safety stock, reorder point, and total inventory cost. Supporting calculations were performed using inventory management analysis procedures to compare the efficiency of the EOQ approach with the existing conventional ordering system.

Result: The results indicate that the enterprise purchased 770 kg of milkfish raw materials with an annual usage of 760 kg and an ordering frequency of 65 times under the conventional system. Using the EOQ model, the optimal order quantity was determined to be 65.25 kg per order with an estimated ordering frequency of 11.65 times per year and an average order cycle of approximately 19.05 days. The recommended safety stock was 12.228 kg, while the reorder point was calculated at 15.648 kg. The implementation of EOQ reduced the total inventory cost to IDR 244,668.75 compared to the conventional system cost of IDR 704,103.75, resulting in a cost saving of IDR 458,435.

Conclusion: The findings demonstrate that the EOQ model provides a practical and efficient approach for improving inventory management in small-scale agroindustries. By determining optimal order quantities and establishing systematic reorder policies, the model helps reduce excessive ordering frequency, minimize inventory-related costs, and prevent raw material shortages that could disrupt production processes. The study highlights the importance of adopting quantitative inventory management tools within small agroindustrial enterprises to enhance operational efficiency and cost control. Furthermore, the results provide empirical evidence that structured inventory planning can significantly improve supply chain stability in small-scale food processing industries. The adoption of EOQ-based inventory management is therefore recommended as a strategic approach to support sustainable production management and operational resilience in small agroindustry systems.