Data Mining Menggunakan Algoritma Apriori untuk Rekomendasi Produk bagi Pelanggan

Data Mining using Apriori Algorithm for Product Recommendation for Customers

Ariefana Ria Riszky  -  Department of Informatics, Universitas Mercu Buana, Indonesia
*Mujiono Sadikin orcid scopus  -  Department of Informatics, Universitas Mercu Buana, Indonesia
Received: 28 Dec 2018; Revised: 12 Jun 2019; Accepted: 12 Jun 2019; Published: 31 Jul 2019; Available online: 4 Aug 2019.
DOI: https://doi.org/10.14710/jtsiskom.7.3.2019.103-108 View
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Section: Original Research Articles
Language: ID
In Volume 7, Issue 3, Year 2019 (July 2019)
Statistics: 1201 460
Abstract
The implementation of a marketing strategy requires a reference so that promotion can be on target, such as by looking for similarities between product items. This study examines the application of the association rule method and apriori algorithm to the purchase transaction dataset to assist in forming candidate combinations among product items for customer recommended product promotion. The purchase transaction dataset was collected in October and November 2018 with a total data of 1027. In the experiment, the minimum value of support is 85%, and the minimum confidence value is 90% by processing data using the Weka software 3.9 version. Apriori algorithm can form association rules as a reference in the promotion of company products and decision support in providing product recommendations to customers based on defined minimum support and confidence values.

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Keywords: apriori algorithm; association rule; product recommendation; data mining; product promotion

Article Metrics:

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