Forecasting the Elderly Population in Songkhla Province Using the Box-Jenkins Method
Keywords:
Elderly, Box-jenkins method, Forecasting, Time series modelAbstract
This research aimed to quantitatively forecast the elderly population in Songkhla province using the Box-Jenkins (Autoregressive Integrated Moving Average - ARIMA) method. This method is based on the assumption that the past behavior of a time series is sufficient to predict future behavior. This study used historical monthly time series data of the elderly population in Songkhla province from 2017 to 2024 to determine the most appropriate ARIMA model. The results showed that the most appropriate model was ARIMA(4,2,0)(2,0,0)12, which exhibits a clear and consistent seasonal pattern (seasonal data). The AIC value was 1181.419, and the estimated variance of error (white noise) was 14188. Projections indicate a significant and continuous increase in the elderly population over the next five years, with an expected rise of more than 50,000 people between 2025 and 2029. The resulting forecast provides a quantitative estimate of the future elderly population size in Songkhla province. The research findings aim to provide valuable insights for local and provincial policymakers in Songkhla for effective resource allocation, health care planning, and development of comprehensive social welfare strategies to address the impacts of an aging society.
References
Ayele, A. W., & Zewdie, M. A. (2017). Modeling and forecasting Ethiopian human population size and its pattern. International Journal of Social Sciences, Arts and Humanities, 4(3), 71-82.
Anvari, S., Tuna, S., Canci, M., & Turkay, M. (2016). Automated Box–Jenkins forecasting tool with an application for passenger demand in urban rail systems. Journal of Advanced Transportation, 50(1), 25-49.
Banchongphatthana, P., & Phantharak, K. (2021). A study and comparison of ARIMA, ARIMAX, and GARCH forecasting models on the SET50 index before and after the COVID-19 pandemic crisis [Master’s thesis]. Thammasat University. (in Thai)
Chanachok, K. (2010). Guidelines for promoting the quality of life of the elderly in Plapak subdistrict administrative organization, Nakhon Phanom province [Master’s thesis]. Khon Kaen University.
Department of Provincial Administration, Ministry of Interior. (2024). Official Registration Statistics System.
Dickey, D. A., & Fuller, W. A. (1979). Distribution of the estimators for autoregressive time series with a unit root. Journal of the American statistical association, 74(366a), 427-431.
Duangjai, K. (2011). Factors affecting the quality of life of the elderly in Lam Sin subdistrict, Si Nakharin district, Phatthalung province [Master’s thesis]. Thaksin University. (in Thai)
Hoksakul, K. (2008). The participation of the elderly in organizing health activities. Chiang Mai University. (in Thai)
Husin, W. Z. W., & Aziz, N. A. (2021). Box-Jenkins model for forecasting malaysia life expectancy. International Journal of Academic Research in Business and Social Sciences.
Hyndman, R., Athanasopoulos, G., & Bergmeir, C., et al. (2023). forecast: Forecasting functions for time series and linearmodels. Retrieved August 28, 2025, from https://pkg.robjhyndman.com/forecast/
IDRUS, N., & MOHAMED, N. (2020). Forecasting the number of airplane passengers using box-jenkins and artificial neural network In Malaysia. Universiti Malaysia Terengganu Journal of Undergraduate Research, 2(4), 89-100.
Jiandon, C., Suwannapong, N., & Boonshuyar, C., et. al. (2011). Quality of life of rural elderly in Wangnamkheaw District, Nakhonratchasima Province. Journal of Public Health, 41(3), 229-239.
Kasem, T., & Tantiphalachiva, K. (1985). Medical care for the elderly. Bangkok: Arun Printing.
Lorchirachoonkul, W., & Jittordwech, J. (2015). Forecasting Techniques. Bangkok: Chulalongkorn University. Press. (in Thai)
Noknoi, J., & Boripunt, W. (2005). A study on the quality of life of the elderly in Songkhla province. Princess of Naradhiwas Univ J. 9(2), 15–27.
Prompak, C. (2013). Aging society of Thailand. Bangkok: The Printing Office of the Secretariat of the Senate.
Rochana, K., & Wongprachan, R. (2025). Statistical models for air quality forecasting: A case study of particulate matter less than 2.5 microns (PM2.5) in Chiang Mai Province. NKRAFA J Sci Technol. 21(2), 242–258.
Songkhla Provincial Development Plan. (2021). Provincial Government Report. Songkhla, Thailand.
Suk-anan, S. (2020). The Promoting Work Strategy for Thai Aging. Journal of Social Synergy. 11(1), 1–17.
Thongyai, K. (2019). Factors affecting the happiness of the elderly in Kaoseng community, Mueang district, Songkhla province. MUT Journal of Business Administration, 16(1), 154-179.
Trapletti, A., & Hornik, K. (2024). tseries: time series analysis and computational finance. R package version 0.10–58.
World Health Organization. (2025). Ageing and health. Retrieved December 22, 2025, from https://www.who.int/news-room/fact-sheets/detail/ageing-and-health
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