Perbandingan Model ARIMA-RBF dan ARIMA-GARCH dalam Peramalan Time Series Inflasi Provinsi Gorontalo


  • Awalia Emiro Program Studi Statistika, Universitas Negeri Gorontalo, Bone Bolango, Indonesia
  • Isran K Hasan Departement of Statistics, Faculty of Mathematics and Natural Sciences, Universitas Negeri Gorontalo
  • Novianita Achmad Program Studi Matematika, Universitas Negeri Gorontalo, Bone Bolango, Indonesia





A quantitative  method that is observed sequentially from time to time is a time series. In the real word, problems often occur where one method is not able to solve the problem. This research used linear and nonlinear methods by combining the ARIMA-RBF anda ARIMA-GARCH models in forecasting, and then the two models were compared based on the MAPE value. This research used monthly data on inflation for housing, water, electricity, and other fuels from 2008 to 2020. The forecast results from the ARIMA-RBF model obtained the MAPE value of 7.5%, and the ARIMA-GARCH model obtained the MAPE value of 11.8%. thus, the best model for predicting inflation in this research was the ARIMA RBF model.


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How to Cite

A. Emiro, I. K. Hasan, and N. . Achmad, “Perbandingan Model ARIMA-RBF dan ARIMA-GARCH dalam Peramalan Time Series Inflasi Provinsi Gorontalo”, Res. Math. Nat. Sci., vol. 2, no. 1, pp. 9–17, Nov. 2022.