Human Resource Information System with Machine Learning Integration

Jake R. Pomperada
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引用次数: 1

Abstract

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. 
与机器学习集成的人力资源信息系统
整合了机器学习的人力资源信息系统,有助管理雇员的档案、分析、周转、数据分析,以及生成政府服务记录使用的电子个人数据表。它是使用有监督的机器学习方法来预测员工离职的。系统还可以生成员工的政府服务记录、服务年限和忠诚奖励、可用休假积分等报表。为了确定开发系统的质量,研究者使用ISO 25010软件质量模型作为评估软件产品属性的基础。将机器学习集成到人力资源信息系统中,对于预测人力资源管理各方面的趋势是非常有用的工具。根据专家和受访者的全面评估,发现人力资源信息系统高度可用,安全,高效,并且提供了一种快速简便的方法来管理员工记录,并使用使用线性回归方法的监督机器学习来预测员工。
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