Assessment of Recruitment Records using Machine Learning

In the era of the fourth industrial revolution (Industry 4.0), the applications of Information Technology (IT) have been widely used in various aspects of life. As the result, analyzing and predicting the result for the application of candidates as well as employers are also growing significantly. Jobseekers and employers want to have accurate information and prediction results in order to have suitable job proposals for themselves and candidates. This research is conducted based on using Machine Learning to meet the requirements of jobseekers and employers in the recruitment evaluation process. We propose to use 4 machine learning methods – Support Vector Machine (SVM), Decision Tree (DT), Random Forest (RF) and Recurrent Neural Network (RNN) to predict job applications. The data set is collected from the Job Center of Binh Duong province. On the basis of the best results method, we build a job application review and visualize the results.