Seminar Nasional Teknologi Informasi Komunikasi dan Industri
2017: SNTIKI 9

COMPARISON OF DISTRIBUTED DATA MINING FOR SELECTION OF THE PROPER MAJORS

Pelsri Ramadar Noor Saputra (STIKOM PGRI Banyuwangi)
Hadiq Hadiq (Unknown)



Article Info

Publish Date
19 May 2017

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.

Copyrights © 2017






Journal Info

Abbrev

SNTIKI

Publisher

Subject

Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Industrial & Manufacturing Engineering Mathematics

Description

SNTIKI adalah Seminar Nasional Teknologi Informasi, Komunikasi dan Industri yang diselenggarakan setiap tahun oleh Fakultas Sains dan Teknologi Universitas Islam Negeri Sultan Syarif Kasim Riau. ISSN 2579 7271 (Print) | ISSN 2579 5406 ...