Exploring School Enrollment Trends in Indonesia Through Time Series Analysis to Inform Counselling and Communication Strategies
(1) Department of Mathematics and Data Science, Universitas Andalas, 25163, Indonesia
(2) Department of Mathematics and Data Science, Universitas Andalas, 25163, Indonesia
(3) Department of Mathematics and Data Science, Universitas Andalas, 25163, Indonesia
(4) Department of Guidance and Counseling, Universitas Negeri Padang, Indonesia
(5) Department of Communication Science, Universitas Andalas, Indonesia
(6) Department of Communication Science, Universitas Andalas, Indonesia
(*) Corresponding Author
Abstract
A time series analysis of School Enrollment Rates across different age groups in Indonesia from 2003 to 2024 was conducted using ARIMA modelling. Data were segmented into four age groups: 7 to 12, 13 to 15, 16 to 18, and 19 to 24 years. Stationarity testing required first-order differencing, and ARIMA models were selected based on autocorrelation and partial autocorrelation structures. The ARIMA(1,1,0) model showed the best fit for the younger groups, capturing the gradual and predictable participation trends influenced by long-term education policies and stable school enrollment patterns. Forecast accuracy was evaluated using Mean Absolute Percentage Error (MAPE) and Mean Squared Error (MSE), revealing excellent accuracy for ages 7 to 12 with MAPE 0.036 percent and MSE 0.001, and for ages 13 to 15 with MAPE 0.089 percent and MSE 0.008. Forecasts for ages 16 to 18 showed moderate accuracy, while results for 19 to 24 indicated greater variability. These findings inform the development of age-specific guidance counselling and public communication strategies to address distinct educational challenges. The study underscores the utility of interpretable forecasting models in supporting evidence-based education policy and planning.
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DOI: 10.24036/0001299chr2025
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