<![CDATA[Inventories system not only could help business to run smoothly, but also to manage organization resources more efficiently. Moreover, the problem regarding inventories are stock differences, between written with the existing stock on warehouse. As a result this could cause financial losses, and if this problem continues, it will makes company's performance decline. One of the causes of stock differences is less regularly stock opname. Therefore, required a physical Inventories system that can help in classification based on the demand level and selection of priority items for the company to perform regularly stock opname. To solve these problems, this research focus to design model for grouping goods based on its handling frequency, lead time, stock opname and other crucial criteria based on company characteristic. We would developed a physical inventory information system using the ABC-Cycle Counting with classification percentage can be set dynamically. Based on data mining method on transaction of retail company the default percentages for each demand level category for A,B and C) respectively are 79,9%, 15,1% and 5%. In addition, a dashboard was developed to display information of classification based on demand level and recommendations information for checking. The results of this research found that a physical inventory recommendation system can help companies to do stock opname regularly, especially in the selection of goods to be checked according to the demand level, to reduce and prevent stock difference between written with the existing stock on warehouse.]]>
Copyrights © 2018
