A Recommendation System for Internal Business Processes of COBIT 2019 Using Graph Algorithm and Similarity Methods

In the dynamic digital landscape, automating IT management is crucial for organizational success and risk mitigation. This study addresses the challenge of automating IT management based on company goals by proposing a novel recommendation system for internal business processes, grounded in the COBIT 2019 framework. The system employs graph algorithms to map relationships, semantic similarity measurements to align enterprise goals with management objectives, and LSTM combined with TF-IDF methods to analyze and recommend specific activities. Experimental results show that this system optimizes IT management practices, enhances operational efficiency, and ensures regulatory compliance. Additionally, a user-friendly graphical representation of internal business processes using Neo4j enables stakeholders to visualize complex relationships within the COBIT framework, facilitating informed decision-making. This research advances IT governance practices by providing organizations with a valuable tool to automate and improve IT strategies, effectively achieving business objectives.