Forecasting Omset Printing of Printing Sales in CV Sembilan Jaya with Neural Network Method

Reni Vivit Ayu Mawarti, Wiwiet Herulambang, R. Adityo
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Abstract

Forecasting is a process for estimating several needs in the future which includes needs in order to meet thedemand for goods and services. Neural Network Backpropagation Method is a time series forecasting method. Thepurpose of this study is to predict the turnover results in the next period obtained by CV. Nine Jaya every week. Thisstudy uses sales data obtained from the printing of food boxes, shoe boxes, watch boxes from January 2014 toDecember 2018. The results of this forecasting are done using the Neural Network method, the smallest MSE valueobtained is 0.004211 with 1000 times iteration and learning rate 0.2. The MSE value obtained meets the condition orcondition value as a good forecasting method because it is able to meet the MSE value requirement <0.1.
用神经网络方法预测胜美兰印品销售的预印量
预测是估计未来几种需求的过程,其中包括满足对商品和服务需求的需求。神经网络反向传播方法是一种时间序列预测方法。本研究的目的是通过CV来预测下一时期的离职结果。每周九次。本研究使用2014年1月至2018年12月食品盒、鞋盒、手表盒印刷的销售数据。采用神经网络方法进行预测,迭代1000次,学习率0.2,得到最小的MSE值为0.004211。得到的MSE值满足条件或条件值是一种很好的预测方法,因为它能够满足MSE值<0.1的要求。
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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