From Walking Libraries to Answer Engines: Optimizing Knowledge Internalization in Public Financing with RAG-Based AI Chatbots - Saragih, Debrian Ruhut; Anggadwita, Grisna (Pusat Penerbitan dan Publikasi Ilmiah, FEB, Universitas Muslim Indonesia, 2026)
This research arises from the critical need to optimize knowledge internalization within the SECI Model, especially in organizations handling complex and regulated information such as public financing. The study aims to identify the limitations of the existing Knowledge Management System (KMS), implement a Retrieval-Augmented Generation (RAG)-based AI Chatbot prototype, and evaluate its effectiveness in facilitating knowledge internalization. A qualitative case study approach was employed using the Design Science Research Method (DSRM). Data were collected through in-depth interviews and prototype testing involving 10 purposively selected respondents from the Public Financing Division of PT SMI. Findings indicate that the conventional KMS is suboptimal, leading to high dependency on social learning and the