<![CDATA[Risk management in software engineering projects describes an integrated design with methods, processes, and artifacts that continuously identify, analyze, control, and monitor risks, to prevent the project from failing. Agile methodology is an alternative to the traditional sequential software development process. Scrum is the most frequently used method based on the 2016 Agile development survey results. In recent years, there have been many studies that have produced a risk management framework for Scrum. However, risk analysis and the selection of responses to risks become a burden for stakeholders, so a framework is needed that can become a support system to help make decisions. This paper uses a comparative study of risk management framework literature and literature that utilizes tools for risk management. The research resulted in a new framework that integrates datasets and machine learning into a risk management framework, so further work can be done to test the effectiveness of the new framework]]>
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