Sciweavers

Share
ASIAMS
2009
IEEE

Uncovering Hidden Information Within University's Student Enrollment Data Using Data Mining

8 years 4 months ago
Uncovering Hidden Information Within University's Student Enrollment Data Using Data Mining
To date, higher educational organizations are placed in a very high competitive environment. To remain competitive, one approach is to tackle the student and administration challenges through the analysis and presentation of data, or data mining. This study presents the results of applying data mining to enrollment data of Sebha University in Libya. The results can be used as a guideline or roadmap to identify which part of the processes can be enhanced through data mining technology and how the technology could improve the conventional processes by getting advantages of it. Two main approaches were used in this study, namely the descriptive and predictive approaches. Cluster analysis was performed to group the data into clusters based on its similarities. For predictive analysis, three techniques have been used namely, Neural Network, Logistic regression and the Decision Tree. The study shows that Neural Network obtains the highest results accuracy among the three techniques.
Fadzilah Siraj, Mansour Ali Abdoulha
Added 08 Nov 2010
Updated 08 Nov 2010
Type Conference
Year 2009
Where ASIAMS
Authors Fadzilah Siraj, Mansour Ali Abdoulha
Comments (0)
books