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All Journal Jurnal Masyarakat Informatika JAIS (Journal of Applied Intelligent System) Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer Jurnal Teknik Informatika (JUTIF)
Ali, Rabei Raad
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Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Energy Engineering

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Journal : JAIS (Journal of Applied Intelligent System)

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Data Mining Application Analyzing Customer Purchase Patterns Using The Apriori Algorithm Prayugo, Moh. Lambang; Wibowo, Dibyo Adi; Hidajat, Moch. Sjamsul; Mintorini, Ery; Ali, Rabei Raad
(JAIS) Journal of Applied Intelligent System Vol. 9 No. 1 (2024): Journal of Applied Intelligent System
Publisher : LPPM Universitas Dian Nuswantoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62411/jais.v9i1.10308

Abstract

The study aims to implement Data Mining with Apriori Algorithm and Association Methods (shop cart analysis) to analyze the sales pattern of Kaffa Beauty Shop stores as a case study. Sales information obtained from stores is used to find out the repeated buying habits of cosmetic products. This analysis provides store owners with valuable information to make more useful decisions about product inventory management, marketing strategies, and other aspects of their business. The Apriori Algorithm implementation follows steps including data preprocessing, subsetting, frequent dataset search, and strong association rules (strong Association Rules). The results of the analysis show that there are important purchasing patterns among some cosmetic products that can be the basis of a more effective sales strategy. The study helps understand how data mining and Apriori Algorithms can be applied in business contexts such as Kaffa Beauty Shop stores. Therefore, the results of this analysis are expected to contribute greatly to improving business efficiency and optimizing marketing strategies for store owners and stakeholders. The research is also expected to show the enormous potential of data analysis to support optimal business decision making.
Co-Authors Ajib Susanto Candra Irawan Christy Atika Sari Dibyo Adi Wibowo Eko Hari Rachmawanto Ery Mintorini Gumelar, Rizky Syah Hadi, Heru Pramono Hartono, Matthew Raymond Laksana, Deddy Award Widya Lalang Erawan Moch. Sjamsul Hidajat Mulyono, Ibnu Utomo Wahyu Nabila, Qotrunnada Pratama, Reza Arista Prayugo, Moh. Lambang Wintaka, Aristides Bima