Volume 20 No 9 (2022)
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Human Resource Data Analysis & predictionusing Decision Tree Algorithm and Random Forest
Durga S,Prathusha Perugu,Nidhi Sree D, Venkateswararao Podile ,Mahesh Manohar Bhanushali, Revathi R
Abstract
Due to the complexity and unpredictability of human behaviour in contrastto equipment or other physical
assets, allocating human capital efficiently has always been a challenging task. Because of this issue,
human resource analytics has lately gained prominence. Employee attrition is a fascinating data set to
investigate. Apartfrom the reasons mentioned in the dataset, other factors, such as distance from work,
further education, establishing one’s own business, politics, or relocation, may occur. However, let us do
some analysis and prediction using the dataset that has been provided to us. Before we begin, let us
clarify why we are doing this analysis: discover why a small percentage of workers leave the company
and their satisfaction. The prediction is used to determine which workers will depart from the business.
Future research may concentrate on developing validated models of the suggested theoretical
frameworks and assessing the impact of Evidence-Based Management methods on human resources
and organizational performance
Keywords
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