Diophantine Journal of Mathematics and Its Applications
Vol. 3 No. 1 (2024)

Perbandingan Penerapan Metode VBEOQ dan Metode Persediaan Multi Item Periode Pemesanan Tunggal untuk Meningkatkan Economic Value Added (EVA) Pada Usaha Mikro

Hadi, Muthia Nurul (Unknown)
Triska, Anita (Unknown)



Article Info

Publish Date
30 Jun 2024

Abstract

Every company requires minimum costs in controlling inventory and maximizing the company value. The company value is an investor's perception of the company success level. Therefore, the inventory management system have to contribute to realize these goals. Besides influencing the company value, inventory control is also useful to expedite the company activities. An alternative solution to maximize the company value is by increasing the economic value added (EVA). The change of EVA ΔEVA) can be analyzed using the Value Based Economic Order Quantity (VBEOQ) method which each item is ordered separately. However, in a company may manage many items. In order to overcome this problem, ΔEVA can be analyzed using the multi-item inventory method of a single order period. These two methods are used to analyze EVA in the micro enterprise Depot Tutup Galon X. Based on the analysis, it is found that by using the VBEOQ method and multi item inventory for a single order period increase the ΔEVA as Rp12,629,947,00 and Rp14,355,057,00, respectively. These results indicate that applying the multi-item inventory method for a single order period at Depot Tutup Galon X is better since it increases the ΔEVA larger.

Copyrights © 2024






Journal Info

Abbrev

diophantine

Publisher

Subject

Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Engineering Industrial & Manufacturing Engineering

Description

The DJMA is published twice a year in June and December. This journal is managed by the Mathematics Department of Bengkulu University. The scope of this journal includes the fields of: 1. Mathematics 2. Applied Mathematics 3. Statistics 4. Applied Statistics 5. Computer ...