A Novelty of Data Mining for Promoting Education based on FP-Growth Algorithm
Andysah Putera Utama Siahaan, Ali Ikhwan, Solly Aryza · 2018
The development of education at this time the increasing number of campuses are growing. Therefore every university wants to gain a lot of students in promoting the university. Many ways can be done for the determination of promotional strategies one of them by using techniques that exist in the data mining. The method used in this research by using the FP-Growth Algorithm. The FP-Growth algorithm is one of the alternative algorithms that can be used to select the most common data stack (Frequent Item Set) in a data set. The FP-Growth algorithm is a development of the Apriori algorithm. As for some events in FP-Growth does not generate candidate because FP-Growth has the concept of Tree build in doing Itemset search. This research is done by studying some research which is often considered by great jokes especially marketing part in determining promotion what become its target. Variables used are Last Education, Home Address, Department, Choice Prodi. The Research Result is a software system for implementing The FP-Growth algorithm that uses the FP-Tree Development concept in finding Frequent Itemset.