Decision Support System using Data Mining Method for a Cross Selling Strategy in Retail Stores
| Autor: | Siti Alvi Solikhatin, Mohammad Imron, Imam Tahyudin |
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| Rok vydání: | 2014 |
| Předmět: | |
| Zdroj: | International Journal of Informatics and Communication Technology (IJ-ICT). 3:171 |
| ISSN: | 2722-2616 2252-8776 |
| DOI: | 10.11591/ijict.v3i3.pp171-177 |
| Popis: | A sales transaction dataof a retail company which is collect edevery day is enormous. Very large data will bemore meaning fultoin crease the company’s profitsif itcanbe extracted properly. Based on the research resultsof Andhika, et al[1], ZhangandRuan[6], Herera et al [7], Witten [11], explained that one of the methods that can gather information from the transaction data is the method of association. With this method it can be determined the patterns of transactions performed simultaneously and repeatedly. Thus, it can be obtained amodel that can be used as a reference for cross selling sales strategy. The purpose of this research is to apply data mining association methods of data mining by using apriori algorithm to create a new sales strategy for cross selling. Based on calculations, Association Rule is implemented by applying Confidence value=0.8while the value of Support=0.1 of the defined minimum value, the total result are 77 rules.Keywords: Data Mining, Association, Apriori Algorithm, Cross Selling, Retail Stores |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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