Bayesian Network Predictive Model for Regional Inflation: Case Study of East Kalimantan and Rupiah Exchange Rate

Sabran Jamilah, Syaharuddin Syaharuddin, Vera Mandailina

Abstract


Abstract: This research is important because fluctuations in inflation and exchange rates have a significant impact on regional economic stability. Therefore, the purpose of this study is to apply the Bayesian Network method in forecasting the next five years of inflation data in East Kalimantan based on actual data from 2015-2024. Data was obtained from the Central Bureau of Statistics and Bank Indonesia, then analyzed using MATLAB software. The results showed that the Bayesian Network model was able to predict the upward trend of inflation from 3.95% in 2025 to 4.30% in 2029, as well as the trend of the exchange rate from Rp15,839.20 to Rp18,021.02. The Mean Absolute Percentage Error (MAPE) value for inflation prediction is 29.34%, while for the exchange rate is 6.27%. The implications of the results of this study indicate that the Bayesian Network model is more accurate in predicting exchange rates than inflation, and can be used as a tool for regional economic policy planning to maintain price stability and currency value.

 


Keywords


Bayesian Network, Inflation, Exchange Rate.

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References


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