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Emon Rifa'i
University of KH. bahaudin Mudhary madura
Civil Engineering, Building, Construction & Architecture Computer Science & IT Electrical & Electronics Engineering Industrial & Manufacturing Engineering Mechanical Engineering

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Digital-Based Soybean Raw Material Inventory Optimization Using Economic Order Quantity, Safety Stock, and Reorder Point Methods at Tofu MSME CV XYZ Nuriyanti Arifiyah; Emon Rifa'i; Cristina Beatrice Mallari
International Journal of Science, Engineering, and Information Technology Vol 10, No 2: IJSEIT volume 10 Issue 2 July 2026
Publisher : Universitas Trunojoyo Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21107/ijseit.v10i2.35362

Abstract

Raw material inventory control that ignores actual demand patterns may cause overstocking, stockouts, emergency purchases, and higher operating costs. This study aims to determine the economic order quantity, ordering frequency, safety stock, dynamic reorder point, and relevant soybean inventory costs, and to design a digital inventory control system for Tofu MSME CV XYZ. A quantitative descriptive case-study approach was applied using annual demand of 166,320 kg, an ordering cost of IDR 100,000 per order, a holding cost of IDR 1,600 per kg per year, a two-day lead time, 324 production days, daily demand observations, and monthly and seasonal demand patterns. The results show an EOQ of 4,559.61 kg, rounded to 4,560 kg per order, with 36–37 orders per year and an average interval of 8.88 production days. At a 95% service level, safety stock is 50 kg. The baseline reorder point is 1,077 kg, while the dynamic monthly reorder point ranges from 1,010 to 1,190 kg and reaches 1,210 kg under peak holiday demand. The total relevant inventory cost is IDR 7,375,368 per year. The proposed digital inventory system integrates transaction records, automatic balance updates, monthly reorder points, and safe, reorder, and critical stock alerts. The integrated policy is more economical, measurable, and responsive to seasonal demand variation.
Co-Authors Cristina Beatrice Mallari Nuriyanti Arifiyah