Prediction of Illiteracy Rates in Indonesia Using Time Series

Muhamad Chamdani, Umi Mahmudah, Siti Fatimah


Illiteracy eradication will increase the quality of human resources; therefore, it should be a priority program for every country. This study applies time series analysis to predict illiteracy rates in Indonesia by using data from the Indonesia Statistic Centre from 2003 to 2017. As data on illiteracy rates are non-stationary, a differencing process is required. The results of this study indicate that the best model to predict illiteracy rates in Indonesia is ARIMA (3,3,1), which shows there are three processes of differencing to obtain stationary data. The results indicate that the point forecast of the illiteracy rate in 2025 is 1.51. Further, the results of the forecasting also reveal that over the next ten years there will a downward trend in illiteracy rates in Indonesia, with the average of the forecast points being 2.32 percent. This shows that continuity and commitment to the implementation of illiteracy eradication programs are required.


ARIMA model; forecast; illiteracy; prediction; time series

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