A comparative study on market basket analysis and apriori association technique

Association Rules is one of the data mining techniques which is used for identifying the relation between one item to another. Creating the rule to generate the new knowledge is a must to determine the frequency of the appearance of the data on the item set so that it is easier to recognize the value of the percentage from each of the datum by using certain algorithms, for example apriori. This research discussed the comparison between market basket analysis by using apriori algorithm and market basket analysis without using algorithm in creating rule to generate the new knowledge. The indicator of comparison included concept, the process of creating the rule, and the achieved rule. The comparison revealed that both methods have the same concept, the different process of creating the rule, but the rule itself remains the same.