Open AccessStudent Information System and Performance Retrieval Through Dashboard
Author(s) -
Karempudi Venkata Krishna,
Mayura Kumar,
P. S. G. Aruna Sri
Publication year - 2018
Publication title -
international journal of engineering and technology
Language(s) - English
Resource type - Journals
ISSN - 2227-524X
DOI - 10.14419/ijet.v7i2.7.10922
Subject(s) - computer science , dashboard , point (geometry) , interface (matter) , moment (physics) , information retrieval , data science , data mining , operating system , physics , geometry , mathematics , bubble , classical mechanics , maximum bubble pressure method
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.