global-journal-of-computer-science-and-technology-c-software-data-engineering Global Journal of Computer Science and Technology - C: Software & Data Engineering 0975-4350 0975-4172 Global Journals Publishing Group Incorporated 115942 Employeeas Performance Analysis and Prediction Using K-means Clustering & Decision Tree Algorithm ShamimSM BANGLADESH, Mawlana Bhashani Science and Technology University 15 01 2018 18 C1

Employee is the key element of the organization. The success or failure of an organization depends on the employee performance. Hybrid procedure based on Data Clustering and Decision Tree of Data mining method may be used by the authority to predict the employees’ performance for the next year. This paper presents how data clustering method can be applied for evaluating the employee’s performance as well in decision making process. Different performance evaluation factors like personality, punctuality, tact oral expression etc has been studied. The result of this paper predicts the number of employee those are selected for promotion or designation and discharged according to their performance. This study help to find out the inefficient employee, magnitude of inefficiency and aids to eliminate inefficiencies with a relatively easy to employ framework.

 data clustering data mining decision tree employee’s performance prediction. Full Text

Employee is the key element of the organization. The success or failure of an organization depends on the employee performance. Hybrid procedure based on Data Clustering and Decision Tree of Data mining method may be used by the authority to predict the employees’ performance for the next year. This paper presents how data clustering method can be applied for evaluating the employee’s performance as well in decision making process. Different performance evaluation factors like personality, punctuality, tact oral expression etc has been studied. The result of this paper predicts the number of employee those are selected for promotion or designation and discharged according to their performance. This study help to find out the inefficient employee, magnitude of inefficiency and aids to eliminate inefficiencies with a relatively easy to employ framework.