COMPARISON OF DISTRIBUTED DATA MINING FOR SELECTION OF THE PROPER MAJORS

Pelsri Ramadar Noor Saputra, Hadiq Hadiq

Abstract


The majors in STIKOM PGRI Banyuwangi are Artificial Intellegence, Software Engineering and Networking. The students have a different ability on IQ and talent, so the student must choose the majors according to their ability in the field of interest. Grades start from semester 1 until the semester 4 constitute basic ability to be a consideration in determining the right majors. To overcome this problem, this research uses classification technique, which is comparing several algorithms among others C4.5, Naïve Bayes, KNN, Random Forest, and SVM. This algorithm applies to build classification selection of the proper majors. Pairwise T-Test determine as an accuracy indicator to evaluate the performance of classifiers. Results showed that C4.5 seemed to be the best of five classifiers which had highest prediction result. C4.5 was used to generate data which can be used to classifying student majors in STIKOM PGRI Banyuwangi. And the results of the accuracy of other methods close to the results of the method C4.5.

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Fakultas Sains dan Teknologi

UIN Sultan Syarif Kasim Riau

Jl. HR. Soebrantas KM 18 No. 155 Pekanbaru Riau Indonesia

Website: http://fst.uin-suska.ac.id

Email: sntiki@uin-suska.ac.id