Volume : VII, Issue : I, January - 2018

A Literature Survey on Analysis of Student Academic Results Using Rough K–Means

Teena A. Dorkhande, Leena Patil

Abstract :

 

Educational data mining is mainly care with developing new methods to discover knowledge from educational database for analysing and enhancing the educational organization. One of the biggest challenges is to improve the quality of the educational processes so as to enhance student’s performance. In order to analyse student academic results towards education an attempt to improve record of student. In the existing research the researchers have used classification and clustering data mining technique.

This paper surveys an educational data mining in education system & also previous result predict and analysing base on attributes and condition using Rough K–Means algorithm and WEKA tool. As we know large amount of data is stored in educational database, so in order to get required data to Rough K–means clustering techniques are develop & use. In this research we use dataset as final year Student of Computer Sciences Engineering, PIET College, Nagpur. Using this college can help how many academic students are distinctions, fail and pass. Also can be predicting result of each student base on previous result of those students before get final exam to be failed or low marks.

 

Keywords :

Article: Download PDF   DOI : 10.36106/ijsr  

Cite This Article:

Teena A. Dorkhande, Leena Patil, A Literature Survey on Analysis of Student Academic Results Using Rough K-Means, INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH : Volume-7 | Issue-1 | January-2018

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