The Mining of the association rules are used to find the rules of the association between a combination of items, to detect a collection of attributes that occur together in the often frequency, and establish some rules of the multitudes. Extracting a single association rules, measuring the quality of the generated rules are usually based on a single evaluation criterion alone, that’s confidence factor / predictive accuracy. In this case, the researchers want to know what the difference could affect the outcome from the process of Data Mining. Is there a process of the difference of natural, cultural, temperature or any other so-called parameters or abstract fields that can’t be written in much detail for a database. On the basis of production’s data system used in this Giant MOG to record data and generalizations or by any other name OLAP (On-line Analytical Processing). The database is already displaying processed data specifications, that will be research as well. Association for the method should be harmonized with the Apriori method, because it’s emphasized here again that Giant MOG is a kind of a high department store. So it should be able to utilize all of database information that has accumulated, in order to make the information useful for subsequent decision making.