Penerapan Data Mining Menggunakan Algoritma Apriori Terhadap Data Transaksi Penjualan Bisnis Ritel

Robby Takdirillah

Abstract


Retail business in West Java province ranks fourth most. This indicates that there is an increase in retail business competition followed by an increase in information technology implementation. The problem of stacking stocks that could harm retail store entrepreneurs is quite common; to overcome such a precise sales strategy is indispensable. In determining the right sales strategy requires the availability of useful data and information. In order to be more efficient data of sales transaction can be processed by applying data mining technique. The method applied by researchers to design the program is the approach of knowledge discovery in the database, including data analysis to the determination of the a-priori algorithm. The purpose of this research is to obtain information about the relation between products that support the sales strategy of the sales transaction data. The linkage information between the products can later be used to support the decision of the retail business sales strategy by adjusting the product to be packaged, product offerings to the buyer and the placement of the product. The results showed that the priori algorithm can be used to process the data of sales transactions into new information in relation between products based on testing with Orange tools. The associative rules established are tested using the lift ratio, so it is important to know the association rules among the most powerful products.


Keywords


Apriori Algorithm; Association Rules; Data Mining; Retail Business; Sales Strategy

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References


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