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Applied Mathematics & Information Sciences
An International Journal
               
 
 
 
 
 
 
 
 
 
 
 
 
 

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Volumes > Volume 20 > No. 3

 
   

Soybean Raw Material Inventory Control in the Home Industry: A Case in Kabupaten Simalungun, Indonesia

PP: 685-695
doi:10.18576/amis/200309        
Author(s)
Juli Antasari Br Sinaga, Ika Rosenta Purba, Hisarma Saragih, Try Koryati, Nurhayati Nurhayati, Marto Silalahi, Rajainal Saragih,
Abstract
In this study, we investigated the soybean inventory system at Tahu Tukiran Artomoro Home Industry in Kabupaten Simalungun, Indonesia. Effective raw material inventory control is essential for ensuring operational efficiency and sustainability in home-based industries. Data were collected through interviews and supported by monthly purchase and consumption records for 2023. A descriptive approach combining qualitative analysis with quantitative methods was employed, specifically the Economic Order Quantity (EOQ) model for optimizing ordering policy and the Moving Average method for demand forecasting. The results show that total annual soybean purchases reached 33,800 kg, while consumption was 33,420 kg, indicating a relatively balanced condition with seasonal fluctuations, especially during Ramadan. Before EOQ implementation, ordering occurred 24 times per year, resulting in higher ordering and holding costs. After applying EOQ, the optimal frequency decreased to 17 orders annually, reducing ordering costs by 29.17% and holding costs by 94.17%, demonstrating significant cost efficiency. Furthermore, demand forecasting using the Moving Average method achieved a Mean Absolute Percentage Error (MAPE) of 9.653%, indicating high accuracy and reliability in capturing demand patterns, including seasonal surges. The findings reveal that the previous system relied on intuitive decision-making, leading to inefficiencies. The integration of EOQ and Moving Average improved both cost efficiency and planning accuracy. This study highlights the importance of simple data-based inventory management in micro-scale industries and provides practical insights for improving decision-making and sustainability in traditional small enterprises.

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