Implementation of Fuzzy Inventory Method and Artificial Neural Network in Determining Safety Inventory of Bag Products
Implementasi Metode Fuzzy Inventory dan Artificial Neural Network dalam Menentukan Persediaan Pengaman Produk Tas
DOI:
https://doi.org/10.21070/ups.3910Keywords:
Prediction, Safety Stock, Fuzzy Invetory, Artificial Neural NetworkAbstract
Sales demand always increases every month shortages due to fluctuating demand, therefore it is best to predict demand in order to determine the right demand and inventory. By using the Artificial Neural Network method, it is hoped that PTK MSME demand can be controlled and able to reduce inventory costs. Meanwhile, the aim of the fuzzy inventory method is to create product inventory levels, to help process storage level inventory in order to reduce storage costs. The relationship between these two methods is to determine what the sales demand will be in the next period and what the safe inventory level will be. So that after forecasting demand, sufficient safety stock calculations will be carried out. The results of this research produced an RMSE from the Artificial Neural Network of 45,031 and a safety inventory of bag products using fuzzy inventory of 43,647 pcs.
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