Forecasting for Optimizing New Product Inventory at Nayara Company
- DOI
- 10.2991/978-2-38476-104-3_24How to use a DOI?
- Keywords
- Forecasting; Economic Order Quantity (EOQ); Reorder Point; Safety Stock
- Abstract
Inventories that increase the cost of storage and maintenance also increase the potential for decreasing the quality of raw materials, reducing company profits. However, if there is too little inventory, it will affect profits and the Company will fail to optimize production. Nayara company has problems controlling inventory; there is no inventory control method, resulting in stockpiling of inventory in the warehouse. Nayara company must have a calculation method to optimize production by reducing ordering and storage costs. This study uses the time series forecasting method to find out the lowest MAD, MSE, and MAPE values. The results in this study are known that the Linear Regression with Trend forecasting method is a forecasting method with a smaller error value and produces a safety stock of 109 pcs, the optimal order in one message is 166 pcs, the frequency of ordering is 20 times. And Nayara Company must place an order again when the inventory in the warehouse is 263 pcs left to create a controlled inventory condition.
- Copyright
- © 2024 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Annisa AU - Pepi Zulvia PY - 2023 DA - 2023/09/29 TI - Forecasting for Optimizing New Product Inventory at Nayara Company BT - Proceedings of the Fourth International Conference on Administrative Science (ICAS 2022) PB - Atlantis Press SP - 224 EP - 238 SN - 2352-5398 UR - https://doi.org/10.2991/978-2-38476-104-3_24 DO - 10.2991/978-2-38476-104-3_24 ID - 2023 ER -