skip to main content

Sistem Optimasi Inventory Berbasis Layanan Web Di PT Pelita Biru

*Cristeddy Asa Bakti  -  Magister Sistem Informasi, Universitas Diponegoro, Indonesia
Open Access Copyright (c) 2017 JSINBIS (Jurnal Sistem Informasi Bisnis)

Citation Format:
Abstract

Various types of LPG sold, requiring a precise inventory management, especially the facts on the ground are often encountered uncertainties include uncertainty of demand and the performance cycle. The aim of this research  is to develop  decision making system to optimize inventory by the Economic Order Quantity method based on the Bowersox formula by using the combining of variables for demand uncertainty and performance cycle. The system uses the web service media method for easy access and maintenance with centralized data on the server and users only use the existing browser. The method of categorizing goods uses the category ABC by dividing the type of goods into categories A (very important), B (important) and C (not important). The results provide safe inventory value calculations based on variables of  uncertainty and performance cycles. With the optimization resulting from this system, the company can maintain the availability of the goods by making appropriate arrangements, priorities, and the amount so as to minimize the occurrence of the possibility of excess and lack of stock.

Fulltext View|Download
Keywords: Decision making system; economic order quantity; inventory

Article Metrics:

  1. Bowersox, D., Close D., Hill, M.G. and Bixby Cooper M., 2002. Supply Chain Logistics Management, 298 – 3070
  2. Chen, Y., Li, K.W., Kilgour, D.M., Hipel, K.W., 2008. A case-based distance model for multiple criteria ABC analysis, Computers & Operations Research 35, 776–796
  3. Dennis, A., Wixcom, B.H. and Tegarden, D., 2005. Systems Analysis and Design with UML Version 2.0 An Object-Oriented Approach, USA: John Wiley & Sons, Inc
  4. Eynan, A., Kropp, D. H., 2007. Effective and Simple EOQ-Like Solutions For Stochastic Demand Periodic Review Systems, European Journal of Operational Research, Vol.180, No.3, 1135–1143
  5. Friedman, M. F., 1984. On A Stochastic Extension of The Friedman EOQ Formula, European Journal of Operational Research, Vol. 17, No. 1, 125 – 127
  6. Guo, H., Galligan, P., 2005. The Application of Utility Computing and Web-Services to Inventory Optimization, Proceedings IEEE International Conference on Services Computing (SCC’05)
  7. Hayya, J. C., Harrison, T. P., and Chatfield, D. C., 2009. A SolutionFor The Intractable Inventory Model When Both Demand and Lead Time Are Stochastic, International Journal of Production
  8. Economics, vol. 122, no. 2, 595 – 605
  9. Li-ping, W., 2009. Study on The System Optimization of Inventory Management of SME, International Joint Conference on Artificial Intelligence
  10. Martınez, L.A.M, Zhang, D.Z, 2012. Optimizing Safety Stock Placement and Lead Time in An Assembly Supply Chain Using Bi-Objective MAX-MIN Ant System, Int. J. Production Economics
  11. Qiu, R., Shang, J., Huang, X., 2014. Robust Inventory Decision Under Distribution Uncertainty: A CVaR-Based Optimization Approach, Int. J. Production Economics, vol.12 (3), 215 – 230
  12. Valente, P., Mitra, G., 2007. The Evolution of Web-Based Optimization: From ASP to E-Services, Decision Support Systems 43, 1096 – 1116

Last update:

No citation recorded.

Last update: 2024-03-19 13:56:06

No citation recorded.