Student Information System and Performance Retrieval Through Dashboard

 
 
 
  • Abstract
  • Keywords
  • References
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  • Abstract


    The principle focal point of information mining is to gather diverse information from databases or information ware houses and the data gathered that had never been known, it is legitimate and operational. Instructive establishments can utilize this to keep up all the data of understudy scholastics effectively which is basically imperative. The execution of understudies in their scholastics is a defining moment for their brightest vocation. Foreseeing understudy scholarly execution has been a basic research point in Educational Data Mining (EDM) which utilizes machine learning and information mining methods to look at information from illuminating settings. Estimating understudy scholarly execution is trying since it relies upon different elements. Grouping and Prediction are among the significant procedures in information mining and assumes an essential part in EDM. The requirement for this is to empower the college to mediate and give help to low achievers as right on time as conceivable. In this examination we build up a grouping model usingC4.5 calculation for area savvy execution assessment framework for designing understudies. It additionally brings network between educators, understudies and guardians by keeping them refreshed with their kid execution consistently. The entire framework will be accessible through a protected, online interface inserted in school sit.


  • Keywords


    C4.5 calculation; Decision tree; Instructive Data mining; Performance forecast; Student data framework

  • References


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      [2] Zhibing Liu, Huixia Wang,Hui Zan “Design and implementation of student information management system.” 2010 International symposium on intelligence information processing and trusted computing. 978-0-7695- 4196-9/10 IEEE

      [3] Nikhil Rajadhyax, Rudresh Shirwaikar, Data Mining on Educational Domain, 2012.

      [4] Manasi Kawathekar, Kirti K.Bhate and Pankaj Belgoankar “An Android Application for Student Information System” International Journal of Advanced Research in Computer Engineering & Technology (IJARCET) Volume 4 Issue 9, Sept 2015

      [5] R. R. Kabra And R. S. Bichkar(2011),‖Performance Prediction Of Engineering Students Using Decision Trees‖, International Journal Of Computer Applications (0975 – 8887) Volume 36– No.11, December 2011.

      [6] Baradwaj Brijesh Kumar and Pal Saurabh (2011).Mining Educational Data to Analyze Student Performance. International Journal

      [7] Parneet Kaura, Manpreet Singh, Gurpreet Singh Josanc “Classification and Prediction based Data Mining Algorithms to Predict Slow Learners in Education Sector” Science Direct Procedia Computer Science 57 ( 2015 ) 500 – 508 2015 (ICRTC2015).

      [8] Data Mining: A prediction for Student's Performance Using Classification Method Abeer Badr El Din Ahmed, Ibrahim Sayed Elaraby


 

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Article ID: 10922
 
DOI: 10.14419/ijet.v7i2.7.10922




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