SISFOTENIKA
Vol 2, No 1 (2012): SISFOTENIKA

DATA MINING POTENSI AKADEMIK SISWA BERBASIS ONLINE

Didik Setiyadi (Unknown)
Ali Nurdin (Unknown)



Article Info

Publish Date
12 Jun 2015

Abstract

Abstact: Problem-solving school difficulties in determining the classification of the student's academic potential can be sought through a system of student's academic potential predictive analysis. The results of predictive analysis are useful to carry out the enrichment program and the improvements program in preparation for the race of academics. Systems analysis of this prediction using data mining to determine the classification of students with academic potential classification models through techniques that form the decision tree of C4.5 algorithm. Predicted results are in the form of the rule of academic potential of students who subsequently entered into an online-based system of academic potential. The data on the student report book information academic potential of students who set and approved by the school. The rule is tested the prediction that yielding a prediction of 77.78% and then applied to other data that is testing the data as much as 20 report book data that generate 90% prediction rate. After the rules are received then put into an online-based system of academic potential. Keywords: Academic Potential Students, Data Mining, Information Systems Online, C4.5 algorithm

Copyrights © 2012






Journal Info

Abbrev

st

Publisher

Subject

Computer Science & IT

Description

Jurnal Ilmiah SISFOTENIKA diterbitkan oleh LPPM STMIK Pontianak dan IndoCEISS. Frekuensi Terbit Tengah Tahunan (2 kali dalam setahun, yaitu bulan Januari dan Juli). Topik yang akan dipublikasikan oleh jurnal SISFOTENIKA berhubungan dengan teknologi informasi, komunikasi dan komputer yang berbentuk ...