The human resource information system with machine learning integration was developed to aid in the management of employees’ records, profiling, turnover, data analytics, and the generation of electronic personal data sheets used by the government service records. It was developed with the feature of predicting employee turnover using a supervised machine learning method.  The system can also generate the following reports, namely, the government service record, years of service and loyalty awards, and available leave credits of the employees. To determine the quality of the developed system the researcher used the ISO 25010 Software Quality Model as a basis when evaluating the properties of a software product. The integration of machine learning in the human resource information system proves to be a very useful tool if integrated into a human resource information system to predict trends in the different aspects of human resource management. Based on the thorough evaluation of the experts and respondents, it was found that the human resource information system is highly usable, secured, efficient, and provides a fast and easy way to manage employees' records and predict employees over using a supervised machine learning that uses the linear regression method.