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Della Andina
Universitas Nusa Mandiri
Computer Science & IT

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Implementasi Data Mining Untuk Analisa Data Penjualan Cat Menggunakan Algoritma Apriori dan Fp Growth (Studi Kasus PT.Sumbermas Unggul Nastari) Widi Setiana; Della Andina; Nabhilah Deviani; Numan Musyaffa
Jurnal Larik: Ladang Artikel Ilmu Komputer Vol 1 No 2 (2021): Desember 2021
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (236.131 KB) | DOI: 10.31294/larik.v1i2.674

Abstract

PT.Sumbermas Unggul Nastari provides paint products with a variety of brands. Every day there is a sale of goods transactions that result in a lot of sales transaction data that accumulates. Researchers are interested in implementing and then comparing two association rule algorithms, namely a priori algorithm and FP-Growth to provide minimum support information that best suits the need to produce the highest frequent itemsets. The results obtained are, JAC with 66% support, JB with 66% support, and results that meet the minimum 70% confidence requirements such as If you buy JAC you will buy JB with 80% confidence, If you buy JB you will buy JAC with 100% confidence.
Co-Authors Nabhilah Deviani Numan Musyaffa Widi Setiana