设计一种商业情报系统,使用数据挖掘方法和立方体分析面包店产品的市场

Rina Fitriana, J. Saragih, Besty Afrah Hasyati
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引用次数: 4

摘要

商业智能系统的作用是为面包房市场部门的决策者提供准确、有用的信息。本研究的目的是设计商业智能模型来分析营销产品,设计数据挖掘模型,测量和分析他们销售的产品的营销过程。本研究的方法是分析系统需求,设计统一的建模语言,进行流程提取、转换和加载,设计数据仓库,并与web集成数据挖掘,形成一个基于web的分析过程多维数据集。生成的商业智能模型是一个营销数据挖掘模型,并将其集成到一个分析过程多维数据集中。在线分析过程立方体的结果是R面包店的交易数据仓库。在设计数据挖掘时,采用k均值聚类方法。数据挖掘k-means聚类的结果是,聚类1占83%,聚类2占17%。集群1是低剩余面包的分类,集群2是高剩余面包的分类。该模型包括最近,频率,货币和客户生命周期价值,结果在R面包店的销售额中排名第一。关键词:商业智能系统,数据挖掘,提取变换负载,在线分析过程立方体
本文章由计算机程序翻译,如有差异,请以英文原文为准。
PERANCANGAN MODEL SISTEM INTELIJENSIA BISNIS UNTUK MENGANALISIS PEMASARAN PRODUK ROTI DI PABRIK ROTI MENGGUNAKAN METODE DATA MINING DAN CUBE
Business intelligence systems participate to deliveran accurate and useful information to decision makers in marketing division of bakeries manufacture . The purpose of this study was to design business intelligence model to analyze the marketing product, de sign the data mining model,  measure and analyze the marketing process of the product they sell . The methodology of this research was to analyze system requirements, design unified mod eling language, make process extract, transform, and load, design data warehouse, and data mining that integrate d with the o n l ine a nalytical p rocess cube webbased . The business intelligence model produced was a marketing data mining model and o n l ine a nalytical p rocess cube. The result from on line analytical process cube was the data warehouse of transaction in R Bakery. In designing the data mining, K-means clustering method was used. The results from data mining k-means clustering were there were 83% cluster 1 and 17% cluster 2. Cluster 1 wasthecategorize for low leftover breads and cluster 2 was the categorize for high leftover breads. The model cub e recency, frequency, and monetary and customer lifetime value resulted rank ed out of the most amount of sales in R Bakery. Keywords: business intelligence system, data mining, extract transform load, on line analitical process cube
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