对智能手机销售预测的线性回归方法的使用

Tri Indarwati, Tri Irawati, Elistya Rimawati
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引用次数: 18

摘要

准确有效地规划和分析市场需求是实现公司成功所必需的。在实践中,现有的交易数据可以作为规划和分析市场需求的参考。这家公司需要一种预测未来销售的工具。这些信息是必要的,因为一个好的销售预测将有助于了解哪些产品必须根据市场需求进行分销,这样公司就可以减少决策中的不确定性。本研究的目的是建立一个信息系统,可以用线性回归方法对82 Cell麻阳的智能手机销售进行预测。该销售预测系统采用线性回归方法,目标是通过观察广告费用和销售数量来确定某一时期的销售量,从而建立一个销售预测系统。研究方法包括观察法、访谈法和文献研究法。使用DAD进行设计包括实体关系图、上下文图、输入过程输出层次图和数据流图。使用的编程语言是Visual Basic。Net和sql server 2008数据库。销售预测应用程序的功能包括处理数据项、客户数据、来料产品数据、销售数据和预测数据。测试结果表明,MAPE值为0.032,MSE值为5.16。从这个值可以看出,用线性回归方法对82 Cell麻阳智能手机销量的预测是非常好的。而在进行的黑盒测试中,Sukoharjo 82 Cell Mayang的智能手机销售预测系统运行良好。关键词:预测,销售预测,进料数据,线性回归,visual basic
本文章由计算机程序翻译,如有差异,请以英文原文为准。
PENGGUNAAN METODE LINEAR REGRESSION UNTUK PREDIKSI PENJUALAN SMARTPHONE
Planning and analyzing market needs precisely and efficiently if managed optimally is needed to achieve company success. In practice, existing transaction data used as a reference in planning and analyzing market needs. This company needs a tool to predict future sales. This information is needed because a good sales prediction will help understand what items must be distributed according to market needs so that companies can reduce uncertainty in decision making. The purpose of this study is to create an information system can do smartphone sales forecasting at 82 Cell Mayang with the Linear Regression method. The sales forecasting system is using the Linear Regression method, The goal to create a sales forecasting system by determining the sales volume with a certain period by looking at the cost of advertising and the number of sales. The research method used includes observation, interviews and literature studies. Designing using DAD includes entity relation diagrams, context diagrams, the hierarchy of input process output and data flow diagrams. The programming language used is Visual Basic.Net and the sql server 2008 database. Features in the sales forecasting application include processing data items, customer data, incoming product data, sales data, and forecasting data. The test results show the MAPE value is 0.032 and the MSE value is 5.16. From this value, it can be said that the prediction of smartphone sales with the Linear Regression method on 82 Cell Mayang is categorized as very good. Whereas for the blackbox testing that has been carried out, it shows that the smartphone sales forecasting system in 82 Cell Mayang, Sukoharjo has been going well.Keywords: forecasting, sales prediction, incoming product data, linear regression, visual basic
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