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All Journal Jurnal Riset Informatika
Ihsan Aulia Rahman
Universitas Nusa Mandiri
Computer Science & IT

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Implementation of the Association Method in the Analysis of Sales Data from Manufacturing Companies Andri Agung Riyadi; Fachri Amsury; Nanang Ruhyana; Ihsan Aulia Rahman
Jurnal Riset Informatika Vol 5 No 1 (2022): Priode of December 2022
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34288/jri.v5i1.491

Abstract

The company produces sales data every day. Over time, the data increases, and the amount becomes very large. The data is only stored without understanding the benefits that exist from these data due to limitations in proper knowledge in analyzing the data, especially transaction data. Sale. To overcome these problems, a study focused on reprocessing sales transaction data in 2018 with a data mining technique approach using the Knowledge Discovery in Database (KDD) concept using the association method and apriori algorithm and a supporting application, namely RapidMiner. This study aims to help companies find customer buying habits or patterns based on 2018 sales transaction data. The results of this study produce 316 association rules where the best rules are generated on record 309 with PRO 889 & PRO 868 PRO 869 rules.
Implementation of the Association Method in the Analysis of Sales Data From Manufacturing Companies Fachri Amsury; Nanang Ruhyana; Andry Agung Riyadi; Ihsan Aulia Rahman
Jurnal Riset Informatika Vol. 5 No. 1 (2022): December 2022
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1038.868 KB) | DOI: 10.34288/jri.v5i1.201

Abstract

The company produces sales data every day. Over time, the data increases, and the amount becomes very large, and the data is only stored without understanding the benefits that exist from these data due to limitations in proper knowledge in analyzing the data, especially transaction data. Sale. In order to overcome these problems, a study focused on reprocessing sales transaction data in 2018 with a data mining technique approach using the Knowledge Discovery in Database concept using the association method and apriori algorithm and a supporting application, namely RapidMiner. This study aims to help companies find customer buying habits or patterns based on 2018 sales transaction data. The results of this study produce 316 association rules where the best rules are generated on record 309 with PRO 889 & PRO 868 PRO 869 rules.
Co-Authors Andri Agung Riyadi Andry Agung Riyadi Fachri Amsury Nanang Ruhyana