Abstract |
This system is a system that supports the process of determining the minimum stocks and profit margins for retailers. The idea of the system is to build a model that can group retail items into categories of ‘fast moving ‘ and ‘slow moving’ items using k-means clustering. The k-means clustering is used for this project because the number of clusters required in the categorization of retail items are already set. The group of cluster with higher centroids is the ‘fast moving’ retail items while for the lowest centroids is the ‘slow moving’ items.
Keywords: k-means clustering, retail, minimum stock, profit margin.
Keywords: k-means clustering, retail, minimum stock, profit margin.
INTRODUCTION
- There are two main activities in retail business that need to be determined; the amount of retails stocks that should be maintained and the profit margins for each item.
- Both processes are required to categorize retail items into group of ‘fast moving’ and ‘slow moving’ items.
- Fast moving items are items that are selling fast (based on the high percentage of sales for the stocks) whereas slow moving items are items with low percentage sales.
- Clustering is the process of grouping a set of physical or abstract objects into classes of similar objects. A cluster is a collection of data objects that are similar to one another within the same cluster and are dissimilar to the objects in other clusters.
OBJECTIVES
1.To design a system model that can determine the minimum stock of the items and the profit margin.
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2.To implement the k-means clustering techniques in the system model to group the retails items.
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3.
To test the proposed system. |
RESULT
CONCLUSION
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Nur Nabilah Binti Abd Hadi
Final Year Student
Pn.Hasni Binti Hassan
Supervisor