An Investigation of University Students' Success In Common Compulsory Lessons Via K-Means Algorithms

Year 2011, Volume: 6 Issue: 1, 342 - 347, 01.02.2011

Yavuz Ünal Ufuk Ekim Murat Köklü

Abstract

In this study, K-Means, is one of the data-mining techniques, was used. The success analyses of college students who attend in 3 faculties and a collage of Selçuk University in 2009-2010 academic year in common compulsory lessons were performed. Data used in this study was obtained from student affairs of Selcuk University. In Visual Studio 2005 Environment, data-mining modules included in Analysis Services packet in SQL Server 2005 were run over the obtained data. Finally opinions and suggestions were specified.

Keywords

Data mining, Clustering Algorithm, Common Compulsory Lessons, K-means Algorithm, Data mining Algorithms,

Üniversite Ö?rencilerin Ortak Zorunlu Derslerdeki Ba?arylarynyn K-Means Algoritmasy Yle Yncelenmesi

Abstract

Bu çaly?mada veri madencili?i tekniklerinden K-Means kullanylarak 2009-2010 e?itim ö?retim döneminde Selçuk Üniversitesinin 3 fakülte ve bir yüksekokulda okuyan ö?rencilerin ortak zorunlu derslerdeki ba?arylarynyn analizi yapylmy?tyr. Çaly?mada kullanylan ö?renci notlary, S.Ü. Ö?renci Y?leri biriminden ORACLE veri tabany ortamynda alynarak gerekli dönü?ümler yapylmy?tyr. Elde edilen bu verilere SQL Server 2005 programy içindeki "Analysis Services" paketinde bulunan veri madencili?i modülleri, Visual Studio 2005 programy üzerinde çaly?tyrylarak analizleri yapylmy?tyr. Yapylan analizler sonucunda çe?itli fakülte ve yüksekokulda okuyan ö?rencilerin ortak zorunlu derslerdeki ba?arylary kar?yla?tyrylmy?, elde edilmi? anlamly sonuçlardan yola çykylarak görü? ve öneriler belirtilmi?tir.

Keywords

Veri Madencili?i, Kümeleme algoritmalary, Ortak Zorunlu Dersler, K-means algoritmasy, Veri Madencili?i algoritmalary,