• DocumentCode
    263757
  • Title

    Data mining techniques for business intelligence in educational system: A case mining

  • Author

    Khan, Muhammad Asad ; Gharibi, Wajeb ; Pradhan, Santanu Kumar

  • Author_Institution
    Coll. of Comput. Sci. & Inf. Syst., Jazan Univ., Jazan, Saudi Arabia
  • fYear
    2014
  • fDate
    17-19 Jan. 2014
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    In an educational system, monitoring the progress of students academic performance is a challenging issue. Currently there is an increasing interest in data mining and educational systems leading to the development of educational data mining. It helps in evaluating progression in an academic environment. In this paper, we have implemented Apriori algorithm for analysing student´s result data, in order to monitor the progression of academic performance of students for the purpose of making an effective decision by the academic planners. This leads to better results thereby increasing the profitability of the educational institutions specially in the private institutions.
  • Keywords
    competitive intelligence; data mining; educational administrative data processing; educational computing; profitability; Apriori algorithm; business intelligence; educational data mining; educational institutions; educational system; private institutions; profitability; Computers; Itemsets; Maintenance engineering; Business Intelligence; Data mining (DM); educational data mining (EDM); educational systems; knowledge discovery;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Applications and Information Systems (WCCAIS), 2014 World Congress on
  • Conference_Location
    Hammamet
  • Print_ISBN
    978-1-4799-3350-1
  • Type

    conf

  • DOI
    10.1109/WCCAIS.2014.6916559
  • Filename
    6916559