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Abstract
Student Database of STIKOM Dinamika Bangsa contains student data in large and varied
quantities. The data can be processed in order to become more valuable information. This
study aims to determine the relationship patterns among variables on the data graduation
students using data mining techniques, calculated and translated using RapidMiner tools.
Before the mining process is done, the data first pass through the process of cleaning,
selection and transformation. The method used in this research is association rules method
by using algorithm apriori, that is algorithm to determine the highest frequency pattern.
Result of contribution from this research is make rule / rule that can be used decision
maker to be consideration when STIKOM Dinamika Bangsa will do promotion and also
development in certain scope. the establishment of association rule with minimum support
and minimum confidence parameters, resulting in a relationship pattern between the
graduation data and the parent data in the form of association rules. The information
displayed in the form of support and confidence relationship between the variables in the
student's graduation data. The higher the value of confidence and support the stronger the
value of the relationship between attributes.