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
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
