IRJET - Higher Education Access Prediction using Data Mining

International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056
Volume: 07 Issue: 02 | Feb 2020 www.irjet.net p-ISSN: 2395-0072
© 2020, IRJET | Impact Factor value: 7.34 | ISO 9001:2008 Certified Journal | Page 1006
Higher Education Access Prediction using Data Mining
Mukesh chavan1, Kunal borade2, Prashant Bansude3, Shruti Shinde4, Snehal Desai5
1Professor, Dept. of Computer Engineering, MIT Polytechnic, Maharashtra, India
2,3,4,5Diploma in Computer Engineering, Dept. of Computer Engineering, MIT Polytechnic, Maharashtra, India
---------------------------------------------------------------------***----------------------------------------------------------------------
ABSTRACT-This system helps students to perform for the
admission test online and provides collegelistaccordingto the
marks. System main objective is to offer a quick and easy way
to appear the exam and it also provides result immediately
after the exam. Multiple choice examination is conducted to
provide special advantages to the students that can’t befound
anywhere else. This software application is built to check
objective answers in an online examination and allocate
marks to the user after verifying the answer.
Key Words: Student performance, exam, login module,
Registration.
1. INTRODUCTION
Higher Education Access Prediction using Data
Mining System helps the students for appearing for the
Admission test online and appoint college according to the
marks. Its mission is to offer a quick and easy way to appear
the exam and it also Provide the result immediatelyafterthe
exam. which are conducting the multiple-choice type
examination, it can provide special advantages to the
students that can't be found anywhere else.
The working of the project is as follows.
The first page provides several links. TheHomelink
contains several information’s about online aptitude test. It
provides a link to the login page. In the Loginlink a userhave
to login before entering the system. An already registered
user can simply type in hisher valid username and
password, and then click the "Login" button.
The Link Rules and Regulations show some rules and
regulations that should be followed by the user. Logout Link
will help the user to logout.
 This software application is built to check objective
answers in an online examination and allocate marks to
the user after verifying the answer.
 The system requires to store the original answer by the
administrator of the system.
 The admin may insert questions and respective
objective answers in the system.
 When a user begins the test, he/she is provided with
questions and options to mark his answers.
 Once the user enters his/her answers, the system then
compares this answer to original answers provided in
database and allocate marks accordingly.
 The system consists of in-built artificial intelligencethat
verify answers and allocate marks accordingly as good
as a human being.
 According to the mark system provide the college list to
the student.
 Student can give their feedback for all this process.
2. LITERATURE STUDY
a. Higher Education Student using data mining
The higher education study isforstudentadmission
in institutes by using entrance exam test of this software.
This idea of getting we in ‘higher education student dropout
prediction and analysis through education data mining’.
After reading this project paper to decide howtomakeexam
entrance text software to provide entrance exam test for
pass out student. The test is bases on all types question, like
math, science, general knowledge. This software is need for
entrance exam test is score of your 12th and 10th standard.
On the basis of your score to provide exam test.
b. Prediction of college using data mining
The collage attribute is problem for institutions of
education. This project softwareisusingdetailsofcollagesto
provide prediction for collage. Basically, in this software is
provide prediction collage for student. Student is taking a
test and When student end an entrance test in this software
after end this software is provide Prediction of collage for
student like which collage can you get, what collage would
you like to apply. The last 5-year collage cut of and rank of
collages all details is provide by admin.
c. Predicting Students’ Performance
The student performance is basis on him test result and
him score of 12th and 10th. To performance of student to him
get result of collage prediction. Student can apply that
collage which provided by higher education software.
3. SYSTEM ARCHITECTURE
When software will start then software is providing
home page. In home page will display to modules, admin
login and user login and registration form for new users to
provide registration. For login, software needs ID and
Password for both logins. In admin login six small module
(navigations pages) for controlling this software and adding
details, updating details. The studentloginhasfourmodules.
In these modules is provide entrance exam test and display

result of predictions collages. This software is providing
logout option from student and admin for logout of owns
account.
When student will register, that register data is
store in database and provide ID and Password form
student.
Fig 1: System Architecture of HEAP
4. CLASS DIAGRAM
Fig 2: Class Diagram of HEAP

In this software is storing ID of both login module,
questions and entrance exam and basic operations of this
project.
The class diagram is showing all attributes of admin,
user and exam of higher education access prediction using
data mining.
5. MODULES
This website is having 2 major modules with their sub-
modules:
1. Admin Login: Admin would be having a login account.
He can add questions in the system and their respective
answers. The answers are stored as a base for reference
for all to use while checking answers.
a. Add Stream: Admin can add all stream detail.
b. Add College: Admin can add college detail,
Stream and cut off list.
c. Manage College: Admin can update college
detail.
d. Add Question: Admin can add question.
e. View Students: Admin can view student detail.
f. View Feedback: Admin can view all the
feedback given by students.
2. Candidate Registration/ Login: Candidate who is
applying for the test must first create an account in the
system by registeringthemselvesandthencanlogininto
the account to begin with test.
a. Register: Student can register their details.
b. View Result: Student can view their own
details.
c. Take Test: Students can give aptitude test.
d. Marks: Students can view their mark in form
of bar graph with possible stream and
students can view their college list.
e. Feedback: Student can give their feedback
about the whole process.
6. FEATURES
a. The system calculates the score and provides
results instantly.
b. It removes human errors that commonly occur
during manual checking.
c. The system provides an unbiased result.
d. Thus, the system excludes human efforts and saves
time and resources.
e. Reduce the time and cost
f. Paper less examination
g. Answers are verified immediately
h. Accurate results.
7. SEQUENCE DIAGRAM
Fig 3: Sequence Diagram of Student
Fig 4: Sequence Diagram of Admin
8. APPLICATIONS
I. This system can be used in schools, colleges, coaching
and institutes for checking answer sheets.
II. The system can also be implemented in different
organizations that conduct regular exams.
9. ADVANTAGES
a. The system calculates the score and provides
results instantly.
b. It removes human errors that commonly occur
during manual checking.
c. The system provides an unbiased result.
d. Thus, the system excludes human efforts and saves
time and resources.
e. Reduce the time and cost
f. Paper less examination
g. Answers are verified immediately
h. Accurate results.

10. DISADVANTAGES
a. The system must be given proper inputs otherwise
system can produce wrong results.
b. Requires an active internet connection.
11. ACKNOWLEDGEMENT
We are pleased to present “Higher Education
Access Prediction usingDataMining” projectandtakethis
opportunity to express our profound gratitude to all those
people who helped us in completion of this project.
We thank our college forprovidinguswith excellent
facilities that helped us to complete and present thisproject.
We would also like to thank the staff members and lab
assistants for permitting us to use computers in the lab as
and when required.
We express our deepest gratitude towards our
project guide for her valuable and timely advice during the
various phases in our project. We would also like to thank
her for providing us with all proper facilities and support as
the project co-coordinator. We would like to thank her for
support, patience and faith in our capabilities and for giving
us flexibility in terms of working and reporting schedules.
We would like to thank all our friends for their
smiles and friendship making the college life enjoyable and
memorable and family memberswhoalwaysstoodbesideus
and provided the utmost important moral support. Finally,
we would like to thank everyone who has helped us directly
or indirectly in our project.
12. CONCLUSION
The project report entitled "Higher Education Access
Prediction using Data Mining" has come to its final stage.
The system has been developed with muchcarethatitisfree
of errors and at the same time it is efficient and less time
consuming.
The important thing is that the system is robust. Also,
provision is provided for future developmentsinthesystem.
The entire system is secured. This online system will be
approved and implemented soon.
13. REFERENCES
1. Crouch MattJ,“ASP.NET WEBPROGRAMMING”,Pearson
Education, II Edition
2. Elias, M.Awad, "SYSTEM ANALYSIS AND DESIGN",
Galgotia Publication Private Limited, 1994
3. http://www.astiwz.com/project-synopsis abstract-
documentation-
sourcecode.php?pid=198&name=Online%20Examinatio
n%20System&project-mode
4. http://ieeexplore.ieee.org/document/6644088/
5. http://ieeexplore.ieee.org/document/1330923/

IRJET - Higher Education Access Prediction using Data Mining

More Related Content

What's hot (20)

Similar to IRJET - Higher Education Access Prediction using Data Mining (20)

More from IRJET Journal (20)

Recently uploaded (20)

IRJET - Higher Education Access Prediction using Data Mining