Forecasting Public Interest Toward FIFA World Cup 2026 in Indonesia Using Google Trends and ARIMA Model

Authors

DOI:

https://doi.org/10.35870/ijsecs.v6i2.7471

Keywords:

Google Trends, FIFA World Cup 2026, Public Interest, ARIMA, Time Series Forecasting

Abstract

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.

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Author Biographies

  • Eko Tri Asmoro, Indraprasta Pgri University

    Department of Informatics Engineering, Universitas Indraprasta PGRI, South Jakarta City, Special Capital Region of Jakarta, Indonesia.

  • Sri Mardiyati, Indraprasta Pgri University

    Department of Informatics Engineering, Universitas Indraprasta PGRI, South Jakarta City, Special Capital Region of Jakarta, Indonesia.

  • Ulfa Pauziah, Indraprasta Pgri University

    Department of Informatics Engineering, Universitas Indraprasta PGRI, South Jakarta City, Special Capital Region of Jakarta, Indonesia.

  • Munich Heindari Ekasari, STMIK Jakarta STI&K

    Department of Information Systems Department, STMIK Jakarta STI&K, South Jakarta City, Special Capital Region of Jakarta, Indonesia.

References

Abdollahi, A., Ramezaninezhad, R., & Naderi Nasab, M. (2024). The impact of sporting events on sports tourism. Journal of Study and Innovation in Education and Development, 4(3), 136–152. https://doi.org/10.61838/jsied.4.3.8

Adelowo, A. B. (2022). Making FIFA World Cup Qatar 2022 truly healthy and safe: Strategies and legacy for present and future sporting events. TEXILA International Journal of Academic Research, 1–12. https://doi.org/10.21522/TIJAR.2014.SE.22.02.Art001

Albahli, S. (2025). LSTM vs. Prophet: Achieving superior accuracy in dynamic electricity demand forecasting. Energies, 18(2), 278. https://doi.org/10.3390/en18020278

Álvarez-García, O., Sureda-Negre, J., Comas-Forgas, R., & Oliver-Trobat, M. F. (2023). The Spanish population’s interest in climate change based on Internet searches. Humanities and Social Sciences Communications, 10(1), 231. https://doi.org/10.1057/s41599-023-01736-5

Avelar, M., Sousa, Á., & Menezes, A. (2021). The impacts of sport tourism events: The Red Bull Cliff Diving World Series case in the Azores Islands. In Advances in tourism, technology and systems (pp. 64–80). Springer. https://doi.org/10.1007/978-981-33-4256-9_6

Cao, T. (2023). Sports brands and tourism: Unexpected perspectives of mutual development. Modern Economy and Management, 2, 9. https://doi.org/10.53964/mem.2023009

Chen, Z. (2025). Empowering sports in the digital economy: Change, opportunity and the future. Highlights in Business, Economics and Management, 59, 34–39. https://doi.org/10.54097/ddqnsm75

Cheng, Y., & Wu, Y. (2025). The formation mechanism of “sports fandom circle” in the digital media era: An analysis from the perspective of fan emotional dynamic development. PLOS ONE, 20(9), e0330900. https://doi.org/10.1371/journal.pone.0330900

Constantinescu, M., & Ungureanu, L. (2024). Economic effects of sports events in tourism: Case study EURO 2024. Journal of Environmental Management and Tourism, 15(4), 664–672. https://doi.org/10.14505/jemt.v15.4(76).08

Dinis, G., Breda, Z., Costa, C., & Pacheco, O. (2019). Google Trends in tourism and hospitality research: A systematic literature review. Journal of Hospitality and Tourism Technology, 10(4), 747–763. https://doi.org/10.1108/JHTT-08-2018-0086

Erokhin, D., & Komendantova, N. (2024). Analyzing public interest in geohazards using Google Trends data. Geosciences, 14(10), 266. https://doi.org/10.3390/geosciences14100266

Gholipour, H. F., Arjomandi, A., Marsiglio, S., & Foroughi, B. (2020). Is outstanding performance in sport events a driver of tourism? Journal of Destination Marketing & Management, 18, 100507. https://doi.org/10.1016/j.jdmm.2020.100507

Gong, X., Hou, M., Han, Y., Liang, H., & Guo, R. (2022). Application of the Internet platform in monitoring Chinese public attention to the outbreak of COVID-19. Frontiers in Public Health, 9, 755530. https://doi.org/10.3389/fpubh.2021.755530

Höpken, W., Eberle, T., Fuchs, M., & Lexhagen, M. (2019). Google Trends data for analysing tourists’ online search behaviour and improving demand forecasting: The case of Åre, Sweden. Information Technology & Tourism, 21(1), 45–62. https://doi.org/10.1007/s40558-018-0129-4

Horky, T., Clavio, G., & Grimmer, C. (2020). Broadcasting the World Cup: A multinational comparative analysis of broadcast quality in the 2014 World Cup. Soccer & Society, 21(1), 15–28. https://doi.org/10.1080/14660970.2018.1448794

Jun, S.-P., Yoo, H. S., & Choi, S. (2018). Ten years of research change using Google Trends: From the perspective of big data utilizations and applications. Technological Forecasting and Social Change, 130, 69–87. https://doi.org/10.1016/j.techfore.2017.11.009

Kim, Y., & Kim, S. (2026). Exploring consumer cognitive and behavioral engagement on a sport team’s Twitter pages. Communication & Sport, 14(1), 59–90. https://doi.org/10.1177/21674795251330303

Lee Ludvigsen, J. A., & Petersen-Wagner, R. (2023). From television to YouTube: Digitalised sport mega-events in the platform society. Leisure Studies, 42(4), 615–632. https://doi.org/10.1080/02614367.2022.2125557

Lee, Y., & Na, S. (2024). Fear of missing out: An antecedent of online fan engagement of sport teams’ social media. Communication & Sport, 12(5), 908–937. https://doi.org/10.1177/21674795231174565

Lenart, K. (2024). Applications of Google Trends as a data source for statistical models. Acta Universitatis Lodziensis. Folia Oeconomica, 3(368), 69–81. https://doi.org/10.18778/0208-6018.368.04

Liang, T., & Li, S. (2025). Utilizing time series analysis to forecast the growth of mobile payment users and its implications for the digital economy. PLOS ONE, 20(8), e0327811. https://doi.org/10.1371/journal.pone.0327811

Mangono, T., Smittenaar, P., Caplan, Y., Huang, V. S., Sutermaster, S., Kemp, H., & Sgaier, S. K. (2021). Information-seeking patterns during the COVID-19 pandemic across the United States: Longitudinal analysis of Google Trends data. Journal of Medical Internet Research, 23(5), e22933. https://doi.org/10.2196/22933

Mavragani, A. (2020). Tracking COVID-19 in Europe: Infodemiology approach. JMIR Public Health and Surveillance, 6(2), e18941. https://doi.org/10.2196/18941

Mavragani, A., & Ochoa, G. (2019). Google Trends in infodemiology and infoveillance: Methodology framework. JMIR Public Health and Surveillance, 5(2), e13439. https://doi.org/10.2196/13439

Moon, J. W., & Barlev, M. (2024). Google search data for social scientists: A tutorial and best practices [Preprint]. OSF Preprints. https://doi.org/10.31234/osf.io/af7b2

Nuti, S. V., Wayda, B., Ranasinghe, I., Wang, S., Dreyer, R. P., Chen, S. I., & Murugiah, K. (2014). The use of Google Trends in health care research: A systematic review. PLOS ONE, 9(10), e109583. https://doi.org/10.1371/journal.pone.0109583

Papanikos, G. T. (2023). The global media coverage of the 2022 Qatar World Football Cup. Athens Journal of Sports, 10(2), 119–132. https://doi.org/10.30958/ajhspo.10-2-4

Pigman, G. A. (2014). International sport and diplomacy’s public dimension: Governments, sporting federations and the global audience. Diplomacy & Statecraft, 25(1), 94–114. https://doi.org/10.1080/09592296.2014.873613

Stimpson, J. P., Tamirisa, K., Kaholokula, J. K., & Ortega, A. N. (2026). Monitoring public health during the 2023 Maui wildfire using Google search trends. Hawai‘i Journal of Health & Social Welfare, 85(1), 10–16. https://doi.org/10.62547/QCKY9141

Ting, C.-J., & Chen, Y.-J. (2025). Recreational activities and tourism expenditure in Taiwan: An online buzz perspective. Journal of Applied Finance & Banking, 1–12. https://doi.org/10.47260/jafb/1561

Zayed, B. A., Talaia, A. M., Gaaboobah, M. A., Amer, S. M., & Mansour, F. R. (2023). Google Trends as a predictive tool in the era of COVID-19: A scoping review. Postgraduate Medical Journal, 99(1175), 962–975. https://doi.org/10.1093/postmj/qgad012

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Published

2026-08-01

Issue

Vol. 6 No. 2 (2026): AUGUST 2026

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Articles

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Copyright (c) 2026 Eko Tri Asmoro, Sri Mardiyati, Ulfa Pauziah, Munich Heindari Ekasari

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How to Cite

Asmoro, E. T., Mardiyati, S., Pauziah, U., & Ekasari, M. H. (2026). Forecasting Public Interest Toward FIFA World Cup 2026 in Indonesia Using Google Trends and ARIMA Model. International Journal Software Engineering and Computer Science (IJSECS), 6(2), 588-599. https://doi.org/10.35870/ijsecs.v6i2.7471

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