Binar Putri Pratiwi, Rakhmat Arianto, Erfan Rohadi
In this research, the TF-IDF method is used in the application of risk analysis recommendation system at universities based on Natural Language Processing (NLP). Each university has several work units, where each work unit has various activities within a budget year that have several categories of risks associated with the achievement of those activities. Risk analysis for each activity is important in the planning process so that all planned activities can be successfully as the planning. Furthermore, risk management utilizing text classification and this risk analysis will be tested by the Internal Audit Unit as an evaluator of each work unit's activities to determine whether the text classification and risk analysis methods will function effectively. In this research phase, a Data Science-based methodology is adopted, with a primary focus on text data processing through NLP techniques to generate relevant recommendations. The results of this research, through concept validation, can provide recommendations for various activities in higher education based on risk levels. The system developed using the TF -IDF method promises to be applied in higher education institutions that wish to plan activities and prepare for the risk levels of several planned works. © 2024 IEEE.
State Polytechnic of Malang, Malang, Indonesia
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