Machine Learning-Based Knowledge Trend Analysis Using LDA for Strategic Decision-Making - Fajar Muttaqi; Moh Alfaujianto; Pungky Hari Wira Atmaja (Universitas Utpadaka Swastika, 2026)
In the digital economy, Knowledge Management Systems (KMS) often fail to provide actionable insights due to information overload, leaving valuable expertise fragmented and underutilized. This research aims to integrate Machine Learning (ML) to transform passive data into proactive strategic foresight by analyzing knowledge trends. Using a longitudinal dataset of search logs and document metadata, the study implements a text-mining pipeline centered on Latent Dirichlet Allocation (LDA) to extract thematic clusters. The model identified eight distinct knowledge domains, with