PERAMALAN HARGA GABAH DAN BERAS BULANAN DI INDONESIA DENGAN METODE ARIMA DAN METODE HOLT-WINTERS
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Date
2024-01
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Elfitra
Abstract
The Autoregressive Integrated Moving Average (ARIMA) method is a method that
combines Autoregressive and Moving Average forecasting models with differencing,
generally expressed as ARIMA(𝑝, 𝑑, 𝑞). The Holt-Winters method or Triple Exponential
Smoothing is a smoothing method based on three smoothing parameters, each element,
namely α (level), β (trend smoothing), and γ (seasonal index). The ARIMA and Holt-
Winters methods in this research are used for forecasting analysis of monthly prices of
grain and rice in Indonesia with data for the period January 2013 to July 2022. The
study shows that forecasting using the ARIMA method is better than the Holt-Winters
method in this research based on accuracy values smaller RMSE.
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Keywords
Autoregressive Integrated Moving Average, Holt-Winters, grain and rice prices
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