Pencarian Frequent Itemset pada Analisis Keranjang Belanja Menggunakan Algoritma FP-Growth

  • Lusa Indah Prahartiwi Sistem Informasi; STMIK Nusa Mandiri

Abstract

Abstrak: Analisis keranjang belanja (juga dikenal sebagai association rule mining) adalah salah satu metode data mining yang berfokus untuk menemukan pola pembelian dengan mengekstrak asosiasi atau data transaksi dari sebuah toko. Analisis keranjang belanja menemukan produk yang dibeli bersamaan dalam keranjang yang sama. Association rules adalah suatu prosedur untuk mencari hubungan antar item yang ada pada suatu dataset. Penelitian ini menggunakan dataset Supermarket dan pengolahan data menggunakan perangkat lunak Rapid Miner. Metode yang digunakan dalam pencarian frequent itemset adalah Algoritma FP-Growth. Hasil eksperimen menggunakan Algoritma FP-Growth didapatkan bahwa kombinasi beer wine spirits-frozen foods dan snack foods merupakan frequent itemset dengan lift ratio sebesar 2.477.
 
Kata kunci: Analisis Keranjang Belanja, FP-Growth
 
Abstract: Market basket analysis (also known as association rule mining) is one method of data mining that focuses on finding purchase patterns by extracting associations or transaction data from a store. Market basket analysis found products purchased together in the same bucket. Association rules is a procedure for finding relationships between items that exist on a dataset. This research uses Supermarket dataset and data processing using Rapid Miner software. The method used in the frequent itemset search is the FP-Growth Algorithm. Experimental results using FP-Growth Algorithm found that the combination of beer spirits-frozen foods and snack foods is a frequent itemset with an lift ratio of 2,477
 
Keywords: FP-Growth, Market Basekt Analysis

Author Biography

Lusa Indah Prahartiwi, Sistem Informasi; STMIK Nusa Mandiri
Sistem Informasi; STMIK Nusa Mandiri

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Published
2017-12-01
How to Cite
PRAHARTIWI, Lusa Indah. Pencarian Frequent Itemset pada Analisis Keranjang Belanja Menggunakan Algoritma FP-Growth. INFORMATION SYSTEM FOR EDUCATORS AND PROFESSIONALS : Journal of Information System, [S.l.], v. 2, n. 1, p. 1 – 10, dec. 2017. ISSN 2548-3587. Available at: <http://ejournal-binainsani.ac.id/index.php/ISBI/article/view/584>. Date accessed: 30 sep. 2020.