Designing web-based data mining applications to analyze the association rules tracer study at university using a FOLD-growth method
Herman Yuliansyah, Lisna Zahrotun · International Journal of Advanced Computer Research · 2016
IntroductionTracer study is one of strategy made by university to obtain information of graduates, so it can evaluate the educational process, measuring the educational goals and make an improvement in the future and in order to establish where graduates are, do, and what interventions can be made to improve their professional activities and services [1][2][3].Meanwhile, data mining is a process to find patterns and trends conducted with pattern recognition technology, statistical and mathematical techniques to sort out a number of useful data in a data set [4,5].Association rule is a pattern of association among itemsets, it is a fundamental task and is of great importance in many data mining applications [6].One of the algorithms that can be used to determine the rule is fast online dynamic-growth (FOLD-growth).It is a combination of fast online dynamic association rule mining (FOLDARM) and frequent pattern (FP)-growth.Several studies in data mining have been carried out.Babu et al. [7] proposed a tree that is fast and efficient in frequent pattern extraction.