Data is an essential property for everyone. A huge quantity of data is normally obtainable in the global world. There are various repositories to shop the data into data warehouses, databases, information repositories, etc. this huge quantity of data requires transformation to ensure that we get useful information. Data mining defines as a technique to obtain information that concealed from collections of data. There are many major features in data mining which includes evaluation, prediction, classification, clustering, and association. This research use association rule to discover the real the interconnections of the association between the data items in the data transaction. The technique utilizes to discover the rule is the FP-Growth. FP-Growth titled as one of the algorithms used to discover frequent item units in the set of transaction data
On a regular basis, JT Innovators updates the promo products that MISUMI Philippines website offered monthly. Based on the interview, the promo packages that MISUMI products offer are just base on the manual selection method of the top management. With this idea, the researcher proposed a study to apply data mining techniques in their means of producing package products that they regularly offer. Through this, the study of market basket analysis using association rule mining come to realize.
This study aims to produce a simulation utilizing a data mining association rule with the FP - growth algorithm as a reference to determine a list of item deals that offered to customers. The study shows that by implementing data mining with association rule technique can help the organization in selecting customer preferences. It is definitely anticipated that the organization can produce a list of package items that may end up being offered to customers based on the rules produced at competitive prices.
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