Peramalan harga beras IR64 kualitas III menggunakan metode Multi Layer Perceptron, Holt-Winters dan Auto Regressive Integrated Moving Average - Anung B. Aribowo; Dedy Sugiarto; Iveline Anne Marie; Jeany Fadhilah Agatha Siahaan (Faculty of Engineering and Informatics, Universitas Multimedia Nusantara, 2019)
This paper aims to present the analysis of price movements of IR64 quality III at the Cipinang Rice Main Market (PIBC) and the accuracy comparison of forecasting using Multi Layer Perceptron (MLP), Holt-Winters, and Auto Reggressive Integrated Moving Average (ARIMA) method. The data are daily price from 1 January 2016 to 31 May 2018 sourced from PT. Food Station. The analysis shows that the price of IR64 quality III rice tends to rise towards the end of 2016 and 2017. This is related to the decrease in the level of rice supply by January each year which encourages PT Food Station to conduct market operations to control the price of rice in the market. The results of accuracy comparison show that the MLP produces a value of Root Mean Square Error (RMSE) of 5,67, Holt-Winters exponential smoothing with trend and additive seasonal component produces a value RMSE of 70.71 and ARIMA method with parameters (1,1,2) resulted in RMSE values ​​of 58.71. The RMSE values ​​of the MLP method have smaller values ​​than the Holt Winter and ARIMA methods which indicate that the MLP method is more accurate