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Random Forest Algorithms and Prediction of Student Satisfaction in Higher Education Organization

Explore –Journal of Research

                                    Peer Reviewed Journal

     ISSN 2278–0297 (Print)

                                                                                                ISSN 2278–6414 (Online)

                Vol. XIV No. 2, 2022

© Patna Women’s College, Patna, India

                                                         https://patnawomenscollege.in/explore-journal-of-research/

Random Forest Algorithms and Prediction of Student Satisfaction in Higher Education Organization

•    Poonam Singh     •  Bhavana Narain

Received                                   : April 2022

Accepted                                   : May 2022

Corresponding Author   : Poonam Singh

Abstract : Higher education is the basic requirement of today’s youth. Datamining is a domain that works for large datasets. It provides various standard algorithms to get knowledge from a large dataset. It works on structured and unstructured datasets. Prediction of student satisfaction in any educational organization is the first and foremost priority. In past years manual methods were used for surveys of student satisfaction. The arrival of technology has changed the pattern of the survey.

Technology has increased the reach of the organization. In our work, we have used the random forest, the technique of data mining for survey and analysis of student satisfaction in educational organizations. Data collection, preprocessing of data set and feature extraction are done. Dataset is generated by the questioner. We have designed a google form for collecting data.

Keywords : Student, Datamining, Education, Organization, Algorithm.

Poonam Singh

MSIT, MATS University, Raipur, C.G. India

Email-id:  poonam20phd@gmail.com

 

Bhavana Narain

MSIT, MATS University, Raipur, C.G.  India

Email-id: narainbhawna@gmail.com