IRJET- Educational Data Mining for Prediction of StudentsPerformance using Clustering Algorithms

International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056
Volume: 06 Issue: 04 | Apr 2019 www.irjet.net p-ISSN: 2395-0072
© 2019, IRJET | Impact Factor value: 7.211 | ISO 9001:2008 Certified Journal | Page 4218
Educational Data Mining for Prediction of Students Performance using
Clustering Algorithms
Nikita Akhade1, Harshada Tandure2, Priyadarshani Deshmukh3
1,2,3Dept. of Computer Engineering, Sinhgad Academy of Engineering, Pune, Maharashtra, India
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Abstract – The main objective of this paper is to use data
mining methodologies to study student’s performance in end
General appreciation. Data mining provides many tasks that
could be used to study the student performance. In this
research, the classification task is used to evaluate student's
performance and as there are many approaches that are used
for data classification, the decision tree method is used here.
Dimensions categorize it and summarize the relationships
which are identified during the mining process The main
functions of data mining are applying various methods and
algorithms in order to discover and extract patterns of
stored data.
Keyword: Management Information System; Database
Analysis
1. INTRODUCTION
The advent of information technology in various fields has
lead the large volumes of data storageinvariousformatslike
records, files, documents, images, sound, videos, scientific
data and many new data formats. The data collected from
different applications require proper method of extracting
knowledge from large repositories for better decision
making. Knowledge discovery in databases (KDD), often
called data mining, aims at the discovery of useful
information from large collections of data.
1.1 Motivation
The general motivationforStudentperformancesystem
is monitoring the all activities of the college through
website. Data mining technique is used for the student
prediction system.
2 RELETED WORK
College Management System deals with all kind of
student details,academic relatedreports,collegedetails,
course details, curriculum, batch details and other
resource related details too. It tracks all the details of a
student from the day one to the end of his course which
can be used for all reporting purpose, tracking of
attendance, progress in the course, completed
semesters years, coming semester year curriculum
details, exam details, project or any other assignment
details, final exam result; and all these will be available
for future references too. Our program will have the
databases of Courses offered by the college under all
levels of graduation or main streams, teacher or
faculty's details, batch execution details, students'
details in all aspects. This program can facilitate us
explore all the activities happening in the college, even
we can get to know which teacher / faculty is assigned
to which batch, the current status of a batch, attendance
percentage of a batch and upcoming requirements of a
batch. Different reports and Queries can be generated
based of vast options related to students, batch, course,
teacher / faculty, exams, semesters, certification and
even for the entire college.
2.1 LITERATURE SURVEY
1 Data Mining: A predictionforStudent'sPerformance
Using Classification Method: In this paper the
classification method is used to grade the student
performance. There are huge amount of data store in
database. Database contain the information for predict
the student performance. There are many approaches
that are used for data classification.Decisiontreeisused
here.
2 Data Mining onEducationalDomain: educational data
mining define as the area of scientific inquiry centered
around the development of methods for making
discoveries within the unique kinds of data that come
from educational settings , and using those methods to
better understand students and the settings which they
learn in. We have also focused on classification of
students into different categories such as good,average,
poor depending on their marks scored by them by
obtaining a decision tree which will predict the
performance of the students and accordingly help the
weaker section of students to improve in their
academics. We have also found clusters of students for
helping in analyzing student’s performance and also
improvising the subject teaching in that particular
subject. Keywords –Data Mining, Education Domain,
India, Association Rule Mining, Pearson Correlation
Coefficient.

3 Mining Educational Data to Improve Students’
Performance: the main objective of the higherinstitute
is providing the quality of education of itsstudent’s.One
way to achieve highest level of quality in higher
education system is by discovering knowledge for
prediction regarding enrolment of students in a
particular course, alienation of traditional classroom
teaching model, detection of unfairmeansusedinonline
examination, detection of abnormal values in the result
sheets of the students, prediction about students’
performance and so on. The knowledgeishiddenamong
the educational data set and it is extractable through
data mining techniques.
4 Mining Education Data to Predict Student’s
Retention: The results show that some of the machines
learning algorithms are able to establish effective
predictive models from the existing student retention
data.
Prediction models that include all personal, social,
psychological and other environmental variables are
necessitated for the effective prediction of the retentionrate
of the students. The retention of studentswithhighaccuracy
is beneficial for identify the students with low academic
achievements initially. It is required that the identified
students can be assisted more by the teacher so that their
performance is improved in future.
3 DESIGN MODULE
College managementsystem isanintegratedwebapplication
that handles various academic and nonacademic activitiesof
a College/Academic Institute. The system can access by
every students/ faculties/ employees of the institution
through internet connected computers or internet enabled
mobile devices with the aid of his user name and password.
Every user will have a customized home page with his/her
profile management facilities. Through links that displaysin
the home page the user can access different options of the
website assigned to him. Though the systemallowsaccessto
every one there is a significant security risk involved in this
project. To tackle this problem we suggest a modular
structure in the proposed system and a completeisolation of
the financial and administrative modules from the public
portal. Only trusted IPs can access these modules. Web
services will interact to the financial and administrative
modules to fetch necessary information to display in the
public portal. Although a standard password policy will be
followed in the designing of the system to prevent the
possibilities of malicious activities of itching users. A self-
driven module in the proposed system will accomplish the
automated tasks such as Email Alerts, SMS alerts,
Notifications to the administrator etc.
3.1 FEATURES OF PROPOSED SYSTEM
Some of the features of the proposed system are:
1) Student Admission
2) Student Attendance management
3) Student Result Management
4) Staff Attendance Management
5) Staff Timetable Management
6) Function Management
7) User Management
4 PROPOSED METHODOLOGY
Module wise description:
Login module is used to check whether the user is an
authorized person to use the system or not. For this the user
should give the correct user name and password.
The different types of users are:
1) Student
2) Teacher
3) H.O.D.
4) Principal
This module consists of the following sub modules
I. Student Registration Form
II. Student Attendance sheet
III. Student Marks Form
IV. Student ID Form
V. Teacher Detail Form
VI. Teacher ID Form
VII. Timetable Form
VIII. Notice Form
IX. Department Detail Form

X. Other Form
Reports
All the above mentioned data are stored in the back end and
can be retrieved as reports with filtering options. The
Following are the reports can be taken from this system:
1. Student Report
2. Teacher Report
3. Department Detail Report
4. Attendance Detail Report
5. Marks Details Report
6. Feedback Detail Report
7. Timetable Details Report
8. Notice Detail Report
9. Other Report
5 SYSTEM ARCHITECTURE
Fig -1: System architecture
6 SOFTWARE REQUIREMENTS
Operating System : Windows 7/8
Technology : Java (JDK 1.8/+)
Front End : Website
Database : MySQL
7 HARDWARE REQUIREMENTS
 Processor : At Least Pentium Processor
 Ram : 2 GB
 Hard Disk : 1 TB
8 ADVANTAGES
 Easily find the necessary information from the
database.
 Easily create/update/delete the information.
9 CONCLUSION
Student performance system can be used by educational
institute for the grade the student according to their
performance. i.e. administrator can delete/update/edit the
student records. Students can also check their progress
through their login. Management System can be used by
education institutes to maintain the records of students
easily. The student information can be easily available.
10 REFERENCES
[1] D. Kornack and P. Rakic, “Cell Proliferation without
Neurogenesis in Adult Primate Neocortex,” Science, vol.
294, Dec. 2001, pp. 2127-2130,
doi:10.1126/science.1065467.
[2] M. Young, The Technical Writer’s Handbook. Mill Valley,
CA: University Science, 1989.
[3] R. Nicole, “Title of paper with only first word
capitalized,” J. Name Stand. Abbrev., in press.
[4] K. Elissa, “Title of paper if known,” unpublished.

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IRJET- Educational Data Mining for Prediction of StudentsPerformance using Clustering Algorithms