Intelligence Performance in Students’ Absence System with Predicted Information by Data mining Algorithms

Ali Fattah Dakhil (University of Sumer)
Waffa Muhammad Ali (University of Thi-Qar)
Asseel Jabbar Almahdi (University of Thi-Qar)

JAIS (Journal of Applied Intelligent System)
Vol 3, No 2 (2018): Journal of Applied Intelligent System

There are many databases projects used by numerous number of organizations. However, embedding business intelligence, BI, technique is a qualitative impact and quite important factor to improve such project’s results and performance. Modern data mining algorithms have dramatically changed our business work, data model and the way we develop software projects. A database application that manages students’ attendance used in university classes is the objective scope that we adopt and work on in this paper. The main key of interest in this research is to improve such attendance system by participating one of data mining classification technique in which we then have a useful learned information and predicted reports about future students’ attendance. Beside this intelligent trait, our work would be crowned with pictorial analytic results that encourage us to have modern and well-mannered intelligent database application.