Student Progress Analysis and Educational Institutional Growth Prognosis Using Data Mining.Journal: International Journal of Engineering Sciences & Research Technology (IJESRT) (Vol.3, No. 4)
Publication Date: 2014-04-30
Authors : S.Saranya; R.Ayyappan; N.Kumar;
Page : 1982-1987
Keywords : Data mining; Naive Bayes algorithm; GoogleVis; postgresql; EIG Prognosis;
Educational organization is one of the important parts of our society, playing a vital role for growth and development of any nation. Mining educational institution’s information system can prove to be of great use to students as well as to the institution. The proposed system can aid in the betterment of student’s performance by figuring educational, co-curricular, extra-curricular, behavioral and overall performance. Educational institutions can reap from the system- scope of different courses, best performing student, key areas to improve on, job placement issues. Various techniques in data mining such as data cleaning, data integration, and classification and regression analysis are used. The graphical output of the system is made by incorporating GoogleVis in the paper. The system is aimed to develop a faith on Data mining techniques so that present education and business system may adopt this as a strategic management tool.
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Last modified: 2014-05-10 19:13:11