Determining Promotional Package Recommendations Using the Frequent Pattern Growth Algorithm at The Java Cafe

Samsinar Samsinar, Dwi Astuti
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引用次数: 0

Abstract

Data analysis and processing is very important to support business development. One example is The Javanese Café which requires analysis and processing to determine promotional menu package recommendations. To carry out data analysis and processing, of course you need technology to make these activities easier. The technology that can be used to overcome this problem is data mining. Data mining has an association rule method which functions to form association patterns. Researchers also use the FP-Growth algorithm to speed up the data processing process. The sales transaction data processing resulted in 14 association patterns with the highest confidence values and 9 menu items with the lowest support values. Then the results were analyzed again and produced 4 recommendations for promotional menu packages that could be used to support product marketing strategies.
在Java咖啡馆使用频繁模式增长算法确定促销包推荐
数据分析和处理对于支持业务发展非常重要。一个例子是爪哇咖啡馆,它需要分析和处理,以确定促销菜单包的建议。要进行数据分析和处理,当然需要技术使这些活动更容易。可以用来克服这个问题的技术是数据挖掘。数据挖掘有一种关联规则方法,其作用是形成关联模式。研究人员还使用FP-Growth算法来加快数据处理过程。销售事务数据处理产生了14个具有最高置信度值的关联模式和9个具有最低支持值的菜单项。然后对结果进行了再次分析,并提出了4条促销菜单包装建议,可用于支持产品营销策略。
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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8 weeks
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