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A Study of Clustering Algorithm for Student Analysis

Bhawna Janghel1 , Asha Ambhaikar2

Section:Research Paper, Product Type: Journal Paper
Volume-7 , Issue-6 , Page no. 937-940, Jun-2019

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v7i6.937940

Online published on Jun 30, 2019

Copyright © Bhawna Janghel, Asha Ambhaikar . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: Bhawna Janghel, Asha Ambhaikar , “A Study of Clustering Algorithm for Student Analysis,” International Journal of Computer Sciences and Engineering, Vol.7, Issue.6, pp.937-940, 2019.

MLA Style Citation: Bhawna Janghel, Asha Ambhaikar "A Study of Clustering Algorithm for Student Analysis." International Journal of Computer Sciences and Engineering 7.6 (2019): 937-940.

APA Style Citation: Bhawna Janghel, Asha Ambhaikar , (2019). A Study of Clustering Algorithm for Student Analysis. International Journal of Computer Sciences and Engineering, 7(6), 937-940.

BibTex Style Citation:
@article{Janghel_2019,
author = {Bhawna Janghel, Asha Ambhaikar },
title = {A Study of Clustering Algorithm for Student Analysis},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {6 2019},
volume = {7},
Issue = {6},
month = {6},
year = {2019},
issn = {2347-2693},
pages = {937-940},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=4658},
doi = {https://doi.org/10.26438/ijcse/v7i6.937940}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v7i6.937940}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=4658
TI - A Study of Clustering Algorithm for Student Analysis
T2 - International Journal of Computer Sciences and Engineering
AU - Bhawna Janghel, Asha Ambhaikar
PY - 2019
DA - 2019/06/30
PB - IJCSE, Indore, INDIA
SP - 937-940
IS - 6
VL - 7
SN - 2347-2693
ER -

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Abstract

In this paper using k-mean clustering method use for students school academic performance are measured by quarterly exam, half yearly exam, and final exams result. So, by taking the marks of three of exams, we can compare the final result of govt. school data and private school data. By using data clustering technique we can predict which school is best.And try to identify the weak student of particular school and will identify the result of best school.This will lead to the identification of best between private & government school in town.Strategies and techniques of best school will be followed which will help in making the education system better.

Key-Words / Index Term

Data clustering , k-mean, academic performance etc

References

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