Developing an IT-Based Knowledge Sharing System for University IT Units: Integrating Large Model Language
Abstract
Information technology companies in Indonesia face the challenge of high employee turnover, which leads to the loss of important knowledge and has an impact on productivity and innovation. This research aims to develop conceptual knowledge sharing and knowledge sharing systems in university IT units, which do not yet have an integrated system for documenting knowledge. Observations show that the ticketing system used can be optimized as a long-term knowledge sharing platform. The designed model includes strengthening the culture of sharing, utilizing social networks within the organization, applying information technology, reward systems, and the SECI model approach. In addition to knowledge repository features, role systems, documentation automation, search, and collaboration modules, the integration of Large Language Models (LLM) such as ChatGPT is expected to improve information search, documentation automation. LLMs play a crucial role in enhancing user interactions by enabling natural language queries, improving search accuracy, and automating knowledge classification. Moreover, they facilitate knowledge extraction from unstructured data, assist in summarizing key insights, and provide adaptive learning capabilities. By leveraging LLMs, the system can increase efficiency, reduce the time required to find relevant information, and ensure knowledge continuity within the organization.
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