Indonesian Journal of Industrial Engineering & Management
Vol 7, No 1: February 2026

Analysis of Burger Main Raw Material Inventory Control Using the Economic Order Quantity (EOQ) Method and the Just in Time (JIT) Method

Rahmadini, Reny (Unknown)
Nurainun, Tengku (Unknown)
Hartati, Misra (Unknown)
Lubis, Fitriani Surayya (Unknown)
Nur, Muhammad (Unknown)



Article Info

Publish Date
26 Mar 2026

Abstract

Burger Fandawa is an MSME in Pekanbaru that faces problems in managing the inventory of the main raw materials, namely bread, meat, and sauce. The main problem is the uncertainty of demand and inventory irregularities that cause shortages or excess stock, thus disrupting smooth production and cost efficiency. This study aims to analyze the main raw material inventory management method using the Economic Order Quantity (EOQ) and Just In Time (JIT) approaches to determine the most optimal method. The research method used is quantitative analysis based on demand data, ordering costs, storage costs, and lead time of the main raw materials during 2023. The results of the analysis show that the optimal purchase quantity according to EOQ is 236.505 packs of bread, 93.510 kg of meat, and 118.866 kg of sauce, with a total inventory cost of IDR. 2,763,809,416. Meanwhile, the JIT method results in a lower total inventory cost of IDR. 1,142,030,936, with a savings difference of IDR. 1,621,778.48. Based on these results, the JIT method is considered more optimal for managing raw material inventory at Burger Fandawa. The JIT method is more efficient in reducing inventory costs and increasing the effectiveness of managing the main raw material stocks.

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Journal Info

Abbrev

ijiem

Publisher

Subject

Control & Systems Engineering Decision Sciences, Operations Research & Management Engineering Industrial & Manufacturing Engineering

Description

The journal aims to advance the theoretical and applied knowledge of this rapidly evolving field, with a special focus on industrial engineering and management, organisation of production processes, management of production knowledge, computer integrated management of production flow, enterprise ...