工业零售消费者兴趣购买先验数据的算法实现

Pub Date : 2020-07-20 DOI:10.31289/jite.v4i1.3775
Ahmad Fachrurozi, Mufid Junaedi, Jordy Lasmana Putra, W. Gata
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引用次数: 3

摘要

这种数据处理的目的是增加公司的营业额,因为通过了解购买商品的兴趣是如何运作的,公司可以购买除主要产品以外的产品。在增加公司收入方面可以使用数据挖掘过程来完成,其中使用了先验算法和关联技术。有了这种先验算法发现的关联技术,以后可以用作消费者购买商品的模式,本研究使用958个数据的数据存储库,包括45个交易。从所获得的结果来看,名称为Paper Chain Kit 50's Christmas的商品是消费者经常购买的产品,据了解,最常见的组合图案是Retro Spot Paper Chain Kit和Paper Chain Kit 50's Christmas。这样,根据已知的购买模式,公司经理可以预测未来的市场需求,可以计算出必须再生产的商品的库存,以及必须减少库存的商品的库存,并且根据关联的结果,经理可以更好地管理产品的布局。关键词:Apriori算法,销售数据,零售业。
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Algorithm Implementation Of Interest Buy Apriori Data On Consumer Retail Sales In Industry
This data processing has the aim to increase the company's turnover, because by being aware of how the interest in buying goods works, the company can buy products other than the main products that it buys. In increasing company revenue can be done using the Data Mining process, one of which uses a priori algorithm and association techniques. With this a priori algorithm found association technique which later can be used as a pattern of purchasing goods by consumers, this study uses a data repository of 958 data consisting of 45 transactions. From the results obtained goods with the name Paper Chain Kit 50's Christmas is a product that is often bought by consumers and it is known that the most frequent combination patterns are the Retro Spot Paper Chain Kit and the Paper Chain Kit 50's Christmas. So that with known buying patterns, the company manager can predict future market needs, and can calculate the stock of goods that must be reproduced, and goods whose stock must be reduced, and also with the results of the association the manager can manage the layout of the product to be better. Keywords: Apriori Algorithm, Sales Data, Retail.
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