Analisis Tren dan Peramalan Minat Masyarakat terhadap Artificial Intelligence di Indonesia Menggunakan Data Google Trends

Abstract

Artificial Intelligence (AI) has become one of the main technologies driving digital transformation across various sectors, leading to increased public interest in obtaining AI-related information through the internet. This study aims to analyze public interest trends in Artificial Intelligence in Indonesia using Google Trends data, identify the best Autoregressive Integrated Moving Average (ARIMA) model, and forecast public interest for the next 12 months. This research employed a quantitative approach with time series analysis using monthly Google Trends data from July 2021 to July 2026. Data analysis included descriptive statistics, trend visualization, stationarity testing using the Augmented Dickey-Fuller (ADF) Test, model identification through Autocorrelation Function (ACF) and Partial Autocorrelation Function (PACF), model selection based on the Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC), and forecasting. The results indicate that public interest in Artificial Intelligence has shown an increasing trend during the observation period. The ARIMA(1,1,0) model was identified as the best forecasting model, producing the lowest AIC value. Forecasting results suggest that public interest is expected to remain relatively high and stable over the next 12 months. These findings provide useful insights into public attention toward AI and support future studies using digital search behavior data.