Penerapan Algoritma Apriori Untuk Rekomendasi Produk Bagi Pelanggan Toko Online Berbasis Website

Ana Hanapi, Rafika Sari, Mukhlis
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Abstract

Today, almost all activities in various sectors of life have been transformed into digital systems to support various related activities. Consideration of the efficiency of dissemination of information outreach and data management that can be recorded properly is the main reason for switching to a digital system. In the economic sector, global business developments are rife with the use of digital devices in marketing various products to increase marketability. Based on this, this research was conducted to apply the Apriori algorithm association data mining to provide product recommendations for online shop customers. The CodeIgniter framework and the waterfall method are used to build a website-based information system. Sampling data was obtained from transaction data at the Rizvenastore store which was used for the database using MySql. The application of the a priori algorithm can form association rules as a reference in-store product promotions and decision support in providing product recommendations to customers based on predetermined minimum support and confidence values. From testing the system using the black box method, the results obtained for all activities on all actors can run as expected.
为基于网站的网店客户推荐产品的杏算法的应用
今天,几乎所有生活领域的活动都已转变为数字系统,以支持各种相关活动。考虑到信息传播和数据管理的效率,可以适当地记录是切换到数字系统的主要原因。在经济领域,全球商业发展充斥着使用数字设备来营销各种产品以增加适销性。基于此,本研究应用Apriori算法关联数据挖掘为网上商店顾客提供产品推荐。采用CodeIgniter框架和瀑布法构建了一个基于网站的信息系统。采样数据是从Rizvenastore商店的事务数据中获得的,该数据使用MySql用于数据库。利用先验算法可以形成关联规则,作为店内产品促销的参考,并根据预定的最小支持度和置信度值为顾客提供产品推荐的决策支持。通过使用黑盒方法测试系统,所有参与者的所有活动获得的结果都可以按预期运行。
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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