Student Progress Analysis and Educational Institutional Growth Prognosis Using Data Mining

Abstract

 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.

Authors and Affiliations

S. Saranya*

Keywords

Related Articles

 Partial Purification and Characterization of Biosurfactant from Pseudomonas Aeruginosa

 Biosurfactant are an amphiphilic compound produced by various bacteria and fungi which reduces surface and interfacial tensions by accumulating at the interface of immiscible fluids and increase the surface areas...

 AN ANALYSIS ON EFFICIENT PROJECT-MANAGEMENT BY USING PRIMAVERA

Project Controlling uses the data of collection, recording and reporting information to bring Actual performance to planned performance. As larger the as more the complexity is in exchange information on timely basis ge...

 HIGHER EDUCATION SYSTEM-A SURVEY

 India is growing day by day and it becomes the home to institutions for higher education. At the time of independence, we have only few colleges and few universities in India. But now in today’s era we have thousa...

  Optimization of Solvent Extraction of Oil From Wild Bush Mango Seed (Irvingia

 Four operating parameters of the solvent extraction of oil from seed of wild bush mango plant (irvingia gabonensis) using normal hexane as the solvent have been optimized by a composite design. A linear model was...

DETECTION OF COMPUTER VIRUSES USING WELM_ FGA_ FBFO

Computer viruses are big threat for our society .The expansion of various new viruses of varying forms make the prevention quite tuf f .Here we proposed WELM_FGA_ FBFO to detect computer viruses. The proposed method...

Download PDF file
  • EP ID EP95393
  • DOI -
  • Views 62
  • Downloads 0

How To Cite

S. Saranya* (30).  Student Progress Analysis and Educational Institutional Growth Prognosis Using Data Mining. International Journal of Engineering Sciences & Research Technology, 3(4), 1982-1987. https://europub.co.uk/articles/-A-95393