IMPLEMENTASI DATA MINING DENGAN ALGORITMA APRIORI UNTUK MENENTUKAN MEREK SEPATU YANG DIMINATI PADA MAHASISWA PASCASARJANA KELAS 14.1A.01 STMIK NUSA MANDIRI JAKARTA

Rezkiani Rezkiani

Abstract


Information technology is more advanced and there is always the very development has an important role in all aspects of life, one aspect that can not be separated from the information technology aspects of the economy is mainly in product sales system, for example of footwear products. Shoes is clothing that is needed for daily activity. The number of sales transactions that occurred during the day showed the amount of consumer interest towards shoes. This led the producers pull out and create a wide variety of innovations, such as brand shoes. Brand is very influenced people to buy a product. Need a creativity and innovation of producers to sales of its products could be improved, let alone see people now who have a high level of consumption of the new goods. There are various ways to anticipate that the products we sell can be increased and in demand by consumers. One way is to use data mining techniques in this case using apriori algorithm (association data mining). This will establish apriori algorithm frequent itemset as predetermined by two parameters, support and confidence, to find an association rule between a combination of items. The process begins with the preparation done preprocessing of data through the data and then transformed into a form that can be processed in the next process is the join and purne until the information of association rules. In the case of this technique apriori data mining algorithms can be implemented on search interest in a brand shoes with the data used is 32 respondents and 20% minimum support and minimum confidence of 60%. The combination of items that meet the requirements of support and confidence is if you buy Nike Adidas will buy the 25% minimum support and minimum confidence of 80%, if you buy Converse Adidas will buy the 25% minimum support and minimum confidence 66.67%.

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