Forecasting Public Interest Toward FIFA World Cup 2026 in Indonesia Using Google Trends and ARIMA Model - Eko Tri Asmoro; Sri Mardiyati; Ulfa Pauziah; Munich Heindari Ekasari (Lembaga Komunitas Informasi Teknologi Aceh (KITA), Indonesia, 2026)
Public interest in major international sporting events can be examined through online search behavior, which provides an indication of public attention and anticipation. This study aimed to analyze and forecast public interest in the FIFA World Cup 2026 in Indonesia using Google Trends data. Weekly search data from June 2021 to May 2026 were collected from Google Trends, focusing on the keyword “FIFA World Cup 2026” and related search terms. A quantitative time-series approach was employed, including descriptive statistics, correlation analysis, the Augmented Dickey-Fuller (ADF) stationarity test, Autocorrelation Function (ACF) and Partial Autocorrelation Function (PACF) analyses, and Autoregressive Integrated Moving Average (ARIMA) modeling. The results showed that search interest increased as the tournament approached, with several notable spikes observed during 2024–2026. Descriptive statistics indicated substantial fluctuations in search activity, while the ADF test confirmed that the series was stationary, with an ADF statistic of −8.1497 and a probability value below 0.05. Several ARIMA specifications were evaluated, and ARIMA(1,0,2) was identified as the selected forecasting model based on the lowest Akaike Information Criterion (AIC = 8.1480) and Schwarz Criterion (SC = 8.2162) values. Forecast evaluation produced an RMSE of 16.482, an MAE of 10.525, and a Theil Inequality Coefficient of 0.571. The forecasting results suggest that search interest in the FIFA World Cup 2026 will remain elevated as the tournament approaches. These findings indicate that Google Trends data combined with ARIMA modeling can be used to analyze and forecast search-interest patterns related to major international sporting events.