Perbandingan Analisa Market Basket Terhadap Data Penjualan Minimarket Dengan Algoritma Apriori, Fp-Growth, Dan Fuzzy C-Covering

Authors

  • Rifky Novrian Kahar Universitas Pamulang

Keywords:

data mining, market basket analysis, Apriori, Frequent Pattern Growth, Fuzzy C-Covering

Abstract

Perkembangan teknologi informasi telah memberikan kontribusi pada cepatnya pertumbuhan jumlah data yang dikumpulkan dan disimpan dalam basis data berukuran besar (gunung data). Dibutuhkan sebuah metode atau teknik yang dapat merubah gunungan data tersebut menjadi sebuah informasi berharga atau pengetahuan (knowledge) yang bermanfaat untuk mendukung pengambilan keputusan bisnis. Algoritma Apriori, Frequent Pattern Growth (FP-Growth), dan Fuzzy C-Covering merupakan beberapa algoritma dalam data mining yang dapat digunakan pada teknik mining market basket analysis. Dalam penelitian ini penulis akan mencoba untuk melakukan suatu eksperiman untuk menganalisa proses data mining terhadap transaksi penjualan produk di minimarket Indomaret melalui sebuah aplikasi yang menggunakan 3 metode market basket analysis. Hasil penelitian menunjukkan algoritma FP-Growth mampu melakukan proses data mining dengan waktu yang paling cepat dan hasil yang paling akurat.

References

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Published

2021-06-14

Issue

Vol. 6 No. 1 (2021): Machine Learning dan Analisa Big Data untuk Inovasi dan Bisnis

Section

Article

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