<![CDATA[Advancements in information and communication technology (ICT) have significantly driven the adoption of Artificial Intelligence (AI), including in Indonesia. This study aims to analyze public interest trends in AI among Indonesian citizens based on Google Trends data from 2015 to 2025, forecast future trends using the Holt-Winters Exponential Smoothing method, and evaluate the accuracy of the generated forecasting model. The research adopts the Knowledge Discovery in Databases (KDD) approach, involving data selection, preprocessing, pattern exploration, and result evaluation. Data was collected using the keyword “Artificial Intelligence” on the Google Trends platform, limited to the Indonesian region. The analysis reveals a notable rise in public interest since 2021, along with a consistent seasonal pattern each year. The Holt-Winters method effectively models both trend and seasonality, supported by data decomposition visualization and validation through the Augmented Dickey-Fuller (ADF) test. The study also presents a web-based forecasting model developed using the Streamlit framework, enabling interactive application. These findings offer an initial reference for understanding Indonesia’s readiness to adopt AI and serve as input for data-driven national technology policy development. ]]>
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