Employee Appraisal Report Processing using Weka

Abstract

The main objective is to evaluate the appraisal report of an employee using a decision tree algorithm. The decision tree is one of inductive learning method used in artificial intelligence. It is used for data classification and prediction. The data mining applications use the decision tree for information retrieval and information extraction. This paper discuss about the method of applying decision tree for predicting the performance of an employee working in an organization. The decision tree is created by using  WEKA tool which is used to evaluate the performance of an employee by processing the appraisal report of an employee. The processed data is mainly used for giving promotion, yearly increment and career advancement. In order to provide yearly increment for an employee, it should be evaluated by using past historical data of employees. The historical data are stored in the form of ARFF(Attribute-Relation File Format) and the performance are found by testing the attributes of an employee against the rules generated by the decision tree classifier in WEKA tool. This paper concentrates on collecting data about employees, generating a decision tree from the historical data, testing the decision tree with attributes of an employee and generating the output as whether to give the promotion or not using WEKA tool. The information about an employee are collected by using the user interface. This information is compared with the trained data stored in the decision tree. The final goal node is to determine whether the employee will get yearly increment, promotion or not.