Pola Beli Konsumen Menggunakan Algoritma Fp-Growth Untuk Rekomendasi Promosi Pada Aneka Jaya Motor

Junta Zeniarja
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引用次数: 1

Abstract

A piece of appropriate information can create and establish a business strategy in increasing sales through technology that can affect the trade-in buying and selling goods with the data information generated can be calculated in detail and accurately. At Aneka Jaya Motor Semarang, this was triggered by the demand for competition. One solution is a product promotion target. For determining which items are feasible for promotion, the application of a promotional decision recommendation system is made using data mining techniques associated with FP-Growth algorithms, its function is to find items that are often purchased simultaneously by consumers. Data used in the form of transaction data with the total amount used 501 data. The results obtained by appearing 1 rule is if consumers buy spark plug parts then buy oil parts with minimum support of 10% and minimum confidence of 35%. The lift ratio obtained is 1 so that valid rules are generated.
消费者购买模式使用Fp-Growth算法用于多元电机的促销建议
一条适当的信息可以创建和建立一个通过技术增加销售额的商业战略,这些技术可以影响商品的买卖交易,生成的数据信息可以详细准确地计算。在Aneka Jaya Motor Semarang,这是由竞争需求引发的。一个解决方案是产品推广目标。为了确定哪些商品适合推广,推广决策推荐系统的应用是使用与FP Growth算法相关的数据挖掘技术进行的,其功能是找到消费者经常同时购买的商品。以交易数据形式使用的数据与使用的总金额501数据。通过出现1条规则得到的结果是,如果消费者购买火花塞零件,那么购买机油零件的最低支持率为10%,最低置信度为35%。所获得的升力比为1,从而生成有效规则。
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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