Peramalan harga beras IR64 kualitas III menggunakan metode Multi Layer Perceptron, Holt-Winters dan Auto Regressive Integrated Moving Average

Dedy Sugiarto, Anung B. Aribowo, Iveline Anne Marie, Jeany Fadhilah Agatha Siahaan
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引用次数: 5

Abstract

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
基于自回归综合移动平均的多层感知器
本文旨在分析广西大米主市场(PIBC) IR64品质III的价格走势,并比较多层感知器(MLP)、Holt-Winters和自动回归综合移动平均(ARIMA)方法预测的准确性。数据为2016年1月1日至2018年5月31日的每日价格,来自PT. Food Station。分析表明,2016年底和2017年底,IR64优质III级大米价格有上涨趋势。这与每年1月的食米供应水平下降有关,这促使PT食物站进行市场运作,以控制市场上的食米价格。精度比较结果表明,MLP的均方根误差(RMSE)为5,67,趋势和季节成分的Holt-Winters指数平滑的RMSE为70.71,参数为(1,1,2)的ARIMA方法的RMSE为58.71。MLP方法的RMSE值小于Holt Winter和ARIMA方法,表明MLP方法更准确
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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