Forecasting food prices in Central Java with the hybrid ARIMAX calendar variation model - Vebryana Wahyuningsih; Putriaji Hendikawati (Songklanakarin Journal of Science and Technology (SJST))
Variations in time series data that occur due to the effects of calendar factors such as holidays, seasons, or differences in the number of days in a month are referred to as calendar variations. Time series problems are not always linear or nonlinear. Instead, they sometimes contain both (linear and nonlinear) at once hence hybrid models can be used to model time series problems. Research was conducted on food prices in Central Java that are affected by calendar variations, namely beef and chicken egg price data. The performance of these methods is compared using RMSE and MAPE accuracy measures. The hybrid ARIMAX-NN and Reg-ARIMA methods produce the smallest RMSE and MAPE values compared to other methods, respectively.