ABSTRACT
In this fast-paced world, choosing a highly qualified and efficient employee that would be appropriate for the job has become a huge challenge. In job sectors, companies and management are concerned about these employees’ performance. Predicting employee performance will be a necessity for companies and a pivotal to success. In this paper, the principal objective is to predict employees’ performance using machine learning. The building of the classification model and identification of the crucial factors that categorically affect the performance was done by two machine learning algorithms: The Random Forest Classifier and K-Nearest Neighbor (KNN). The dataset that was utilized for the to build the model for prediction of the employees’ performance is the IBM HR Analytics Employee Attrition & Performance from Kaggle. This system provides a suitable model which determines the performance and makes it convenient for the HR department to find the most skillful, knowledgeable and efficient employee on their performance report which depends on various factors.
