Analytical method by clustering data mining for performance evaluation

Abstract EN

Data mining deals with the discovery of hidden knowledge, unexpected patterns and new rules from large database, Basically it is concerned with the analysis of data and the use of software techniques for finding patterns in sets of data, one of its main terms is the clustering, which is mean, the process of dividing a database into mutually exclusive groups such that the members of each group are as close as possible to one another , and different groups are as far as possible from one another , where distance is measured with respect to all available variables.

Clustering is perhaps the most frequently used data mining algorithm, being useful in its own right as an exploratory technique, and also as a subroutine in more complex data mining algorithms such as rule discovery, indexing, summarization, anomaly detection, and classification, In the last decade the educational institutions began to apply the standards of quality and accreditation, one of the most important standards is the( Planning and Evaluation) therefore; all the educational institutions activities must be evaluate according to logical and scientific methods, clustering methods have been applied in this research for a real cases concerned with Foundation Technical Institutes (FTE) to have fairly evaluation of performance among FTE branches in giving educational courses to the society(year 2006-2009 ),Complete Linkage method gives perfect and meaningful structure to have analytical method for fairly evaluation of performance to be identical with the standards of quality and accreditation, while the traditional evaluation depends only on the number of courses.