An approach Human Resource Information Systems (HRIS): A Hierarchical Deep Learning Framework for Predicting Employee Satisfaction

The change from traditional techniques of human resource information management to urban computerization approaches was received with discontent by certain government personnel. Still, in this era of computerized governance, this shift is crucial since it improves the efficiency and effectiveness of human resource tasks. In light of this emerging tendency, the government has developed an HRMIS program specifically for use by government agencies. Human Resource Management Information System (HRMIS) is an integrated e-government service that acts as a public sector database and gives government workers a unified interface to do HR-related tasks. The suggested approach consists of two parts: preprocessing and training the model. Transferring data from an unstructured format to one that machine learning systems can work with is the goal of this phase. Data encoding and cleaning are part of the process, as is principal component analysis (PCA) for dimensionality reduction. It was the HDL that we used for training the model. We outperform state-of-the-art alternatives like CNN and DNN with our proposed model, which obtains an average accuracy rate of 93.58 percent.