指数平滑法与线性回归法在预测商品销售额方面的比较

Erwin Panggabean, Anita Sindar Ros Maryana Sinaga, J. Sagala, Alya Sophia Ramadhan, Alpon Josua
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引用次数: 0

摘要

贸易企业是在销售领域开展业务的企业,目的是通过销售活动获取最大利润。为了能够有效地进行销售,需要有一个预测系统,这样才不会出现库存过剩或短缺的情况,销售过程才能顺利进行。在不使用应用预测方法的工具的情况下,人类在解决预测问题上的局限性是找到正确预测值的障碍之一。因此,我们需要一个预测系统,帮助我们准确、快速地找到预测值。因此,问题的提出是如何使用指数平滑法和线性回归法设计和建立一个销售预测系统,然后比较这两种方法,找出哪种方法最好,这两种方法都使用周期性数据预测模型。使用的数据收集方法是从以前的研究和期刊中获取二手数据,以及结合图书馆学习方法,即从与预测相关的书籍、参考文献和科学著作中获取信息。用于构建应用程序的工具是 MS-Visual Studio 2010 和基于 WEB 的系统
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Comparison Of Exponesial Smoothing With Linear Regression Predicting Amount Of Goods Sales
A trading business is a business that operates in the sales sector with the aim of obtaining maximum profits through sales activities. To be able to sell efficiently, a prediction system is needed, so that there is no excess or shortage of inventory and the sales process can run smoothly. Human limitations in solving prediction problems without using tools that apply prediction methods are one of the obstacles in finding the right prediction value. Therefore, we need a prediction system that can help find accurate and fast values. So the problem formulation is how to design and build a sales prediction system using exponential smoothing and linear regression methods, then compare the two and find out which method is the best, both of which use periodic data prediction models. The data collection method used is secondary data from previous research and journals, as well as combining library study methods, namely information obtained from books, references and scientific works related to predictions. The tool used to build applications is MS-Visual Studio 2010 and WEB based system
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