IMPLEMENTASI ALGORITMA ECLAT UNTUK FREQUENT PATTERN MINING PADA PENJUALAN BARANG
| Main Authors: | Samodra, Joseph Eric , Susanto, Budi , Raharjo, Willy Sudiarto |
|---|---|
| Format: | Article PeerReviewed Book |
| Terbitan: |
Universitas Sanata Dharma
, 2015
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| Subjects: | |
| Online Access: |
http://e-journal.uajy.ac.id/10827/1/TFJ859.pdf http://e-journal.uajy.ac.id/10827/ |
Daftar Isi:
- Eclat algorithm is used to find frequent item sets. This algorithm uses a vertical data type and perform depth-first search in the lattice sections and determine the set of items to support cuts transaction list. Research is carried out by comparing the data pattern generated sales Eclat algorithm. The data used is the sales data in 2011 and 2012. Analyzes were performed using the minimum support ranging from 5% to 20%. At a minimum support of 15% and 20% reporting no sales rules. This is because too many variations of groups of goods. The data are too diverse causes minimum support value can not be more than 15%, this is because the average customer bought stuff that was as much as 3 items only. 2010 and 2011 sales data has the same relative pattern of rules seen from the support and lift values. Olie is not found in the rule because most sales Olie is a single sale.