@ARTICLE{Nurprihatin_Filscha_Comparing_2022,
 author={Nurprihatin, Filscha and Rembulan, Glisina Dwinoor and Pratama, Yohanes Dwi},
 volume={vol. 13},
 number={No 4},
 pages={16-25},
 journal={Management and Production Engineering Review},
 howpublished={online},
 year={2022},
 publisher={Production Engineering Committee of the Polish Academy of Sciences, Polish Association for Production Management},
 abstract={Improper planning of inventory will affect the factory operating costs, building costs, the cost of loss, and the cost of product defects due to being stored for too long which will eventually become a loss. This research discusses the processing industry which is experiencing lumpy demand. In carrying out the production process, the company has never made plans for future demand, resulting in a waste of message costs due to repeated orders of raw materials ordered to suppliers. This paper contributes to overcoming this issue by simulating future demand by using the Material Requirement Planning (MRP) method with a probabilistic Economic Order Quantity (EOQ) and Periodic Order Quantity (POQ) model. The demand in the coming period is determined using the Autoregressive Integrated Moving Average (ARIMA) method, and an aggregate plan is carried out to determine the regular cost of raw material production and optimal subcontracting. The final analysis states that the calculation of MRP on the selected items using POQ produces the lowest cost for planning S45C-F, SGT-R, and SKD11-R, while SLD-R uses the probabilistic EOQ method.},
 type={Article},
 title={Comparing Probabilistic Economic Order Quantity and Periodic Order Quantity Model Performance Under Lumpy Demand Environment},
 URL={http://journals.pan.pl/Content/125625/PDF/2_846_corr2.pdf},
 doi={10.24425/mper.2022.142391},
 keywords={Lumpy demand, Material requirements planning, Probabilistic economic order quantity, Periodic order quantity, Aggregate plan},
}