Employee Retainment Prediction Using Text Mining and Opinion Mining 1

Volume 3, Issue 5, May – 2018 International Journal of Innovative Science and Research Technology
ISSN No:-2456-2165
Employee Retainment Prediction using Text Mining

and Opinion Mining
Vasudeva Roa P V1, Shreya2, Zafeera Banu3, Shifali Shetty4, Princia Honey Kundar5
1
(Assistant Professor, Dept. of Information Science Engineering, Sahyadri College of Engineering and Management,
Karnataka, India)
2,3,4,5
(Student, Dept. of Information Science Engineering, Sahyadri College of Engineering and Management,
Karnataka, India)
Abstract:- Performance Monitoring is one of the most employee performance is not a easy task. Earlier it was done
important issues of an organization today. In order to manually which was time consuming and sometimes it
overcome the difficulties of manually monitoring the could be biased. In order to overcome such problems several
performance of an employee, this system has been systems where introduced one of which is Employee
introduced. It enables the monitoring of employee Retainment Prediction System.
perspective based on various aspects related to an
organization. This system takes feedback from the In an organization, the employees are divided into
employee in the form of number of questionnaires. Based different teams and each team has both team members as
on the feedback given by the employee the higher well as team leader. In an Employee Retainment Prediction
authority can estimate the chances of him quitting the System, the feedback is taken from both team member and
organization. Taking into account the probability of team leader. The team member gives the feedback on his
employee leaving the company, appropriate actions can perspective about the organization and team leader gives the
be taken. feedback about the performance of respective team member.
The feedback is taken in the form of several questionnaires’
Keywords:- organization, feedback, questionnaires, as well as a comment box.
comment.
I. INTRODUCTION II. ARCHITECTURE OF THE PROPOSED
SYSTEM
Opinion Mining is a process of determining the human
behavior based on reviews and feedback. Once if you Initially, the team member has to login to the
understand how the human feel after analyzing the reviews Employee Retainment System by entering his user ID,
you can identify what he likes and dislikes. Opinion Mining password and type. If the details are valid then the feedback
can be widely used in determining the movie reviews, page is displayed where he can give the feedback on his
reviews of product marketing, employee performance view about the organization else the error message will be
monitoring, fake review detection etc. It has methods such displayed. After this he can logout from system. The team
as classification, clustering, similarity checking and so on. leader login procedure is similar to that of team member.
Sometimes Opinion Mining is also known as Sentiment Once the team member and team leader are done with
analysis. giving feedback, now the manager can view the result of the
feedback. In order to view the result, the manager has to
Text Mining is a process of extraction of useful data login using his user ID, password and type. If the details are
from large amount of text. In Text Mining, high quality data valid, results will be displayed to him, else the error
is derived from large amount of data by pattern and trend message will pop up.
devising through the means such as statistical pattern
learning. The objective of Text Mining is to exploit the large The feedback given by the team member, team leader
amount of text available in order to discover new patterns and manager will be stored in the database. The feedback is
and trends in data. For Example: Years ago people in given in the form of certain questions as well as a comment
various sector used pen and paper to store data, as the box. The feedback given as questions contribute 90% of the
technology evolved, everything has become digital which result and remaining 10% is of the comment. The questions
results in the creation of large amount of text document. In are answered in the form of yes or no. Here the number of
order to manage and extract the useful data from the large no is represented by z (i.e., zero) and the number of yes is
amount of text, Text Mining is used. represented by o (i.e., one). Each time the yes is clicked o
gets incremented and each time a no is clicked z is
Performance Monitoring of an employee plays a vital incremented. Finally the number of o will be multiplied by
role in the growth of an organization. In order to meet the 10, in order to get the percentage.
goals of an organization, evaluation of employee
performance is very important. But determining the
IJISRT18MY596 www.ijisrt.com 706

ISSN No:-2456-2165
Fig 1:- Architecture Diagram for Employee Retainment System
The comments given by the team member and team placed in a separate file. Compare the words with the
leader contribute the 10% of the result. Initially, the test set and find which words are the positive and negative.
punctuations present in the comments is replaced by the
whitespace. The comment is then divided into parts and
Fig 2:- Modular Diagram for Employee Retainment System
feedback. Here the x-axis represents the number of

III. RESULT AND ANALYSIS words and the y-axis represent the time in milliseconds. We
can see that as the number of word increases, the time taken
The following graph represents the processing time of to process gradually increase.
the Employee Retainment Prediction system based on the
number of words present in the comment section of the
Fig 3:- Graph to represent the processing time of the Employee Retainment Prediction System

ISSN No:-2456-2165
Fig 4:- Screenshot of Home Page

Fig 7:- Screenshot for Team Leader Feedback
The figure above shows the screenshot of how the

team member and team leader gives feedback. The feedback
is in the form of certain questions and the comment.
Fig 5:- Screenshot of login page
The figure 4 represents the home page of the

Employee Retainment Prediction System. The home page
consists of home and login. The figure 5: represents the
login page of the system. The login page consists of user ID,
password and type. Here the team member, team leader
and manager login based on their details.
Fig 8:- Screenshot of viewing Feedback
Fig 9:- Screenshot of Final Result

The figure 8 represents the page that is displayed to the
Fig 6:- Screenshot for Team Member Feedback manager where he can view the end result. The figure 9
represents the end page that displays the final result to the
manager with respect to which he makes the decisions

ISSN No:-2456-2165
IV. CONCLUSION
This paper focuses on estimating the employee

feedback on his perspective about organization along with
the feedback of team leader based on respective employee’s
performance in order to obtain the average feedback. This
overall feedback enables the manager to make the
appropriate decision. The feedback is displayed in the form
of percentage as well as the in the form of good, bad or
average. Our system can currently be used in Computers or
laptops, further it is intended to be used in smart phones as
an application which makes its use more easier.
REFERENCES
Journal Papers:
[1] V. Suriyakumari and A. Vijaya Kathiravan , “An
Ubiquitous Domain Driven Data Mining Approach For
Performance Monitoring in Virtual Organization Using
360 Degree Data Mining And Opinion Mining” 2013
International Conference on Pattern Recognition,
Informatics and Mobile Engineering (PRIME), ISBN c :
978-1-4673- 5845-3.
[2] Manoj Kumar Das, Binayak Padhy and Brojo Kishore
Mishra, “Opinion Mining and Sentiment classification:
A Review”, 2017 International Conference on Inventive
Systems and Control (ICISC), ISBN c : 978-1-5090-
4715-4.
[3] Iyer Aurobind Venkat Kumar and Sanatkumar
Jayantibhai Kondhol Shardaben, “Comparative Study of
data Mining Clustering Algorithms” 2016 International
Conference on Data Science and Engineering(ICDSE),
ISBN c : 978-1-5090-1281-7.
[4] Francis F. Balahadia, Ma. Corazon G. Fernando and
Irish C. Juanantas, “Teacher’s Performance Evaluation
Tool Using Opinion Mining with Sentiment Analysis”,
2016 Region 10 Symposium(TENSYMP), ISBN c
:978-1-5090-0931-2.
[5] Amani A. Abed and Alaa M. El-Halees “Detecting
Subjectivity in Staff Performance Appraisals by Using
Text Mining : Teacher’s Appraisals of Palestinian
Government Case Study ”,2017 Palestinian
International Conference on Information and
Communication Technology(PICICT), ISBN c :978-1-
5090-6538-7.
[6] Kavitha Karun A, Mintu Philip, Lubna Ki
,“Comparative Analysis of Similarity Measures in
Document Clustering” ,2013 International Conference
on Green Computing, Communication and
Conservation of Energy (ICGCE), ISBN c :978-1-4673-
6126-2.
[7] Tejshree D. Chungade, Prof. Shweta Kharat,
“Employee Performance Assessment in Virtual
Organization using Domain-Driven Data Mining and
Sentiment Analysis”,2017 International Conference on
Innovational in Information Embedded and
Communication Systems 978-1-5090-3294-5.
[8] Sohail Ahmed, Xing KE, “Human Resource
Management: Employees Career Development Impact
on Organizational Performance”,2016 978-1-5090-
2842-9.

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Volume 3, Issue 5, May – 2018 International Journal of Innovative Science and Research Technology

Employee Retainment Prediction using Text Mining

IJISRT18MY596 www.ijisrt.com 706

Fig 1:- Architecture Diagram for Employee Retainment System

Fig 2:- Modular Diagram for Employee Retainment System

feedback. Here the x-axis represents the number of

IJISRT18MY596 www.ijisrt.com 707

Fig 4:- Screenshot of Home Page

The figure above shows the screenshot of how the

Fig 5:- Screenshot of login page

The figure 4 represents the home page of the

Fig 9:- Screenshot of Final Result

IJISRT18MY596 www.ijisrt.com 708

This paper focuses on estimating the employee

IJISRT18MY596 www.ijisrt.com 709

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