PENERAPAN ASSOCIATION RULE MINING (ARM) DENGAN ALGORITMA FP-GROWTH UNTUK MENEMUKAN POLA DATA PENJUALAN BARANG KOPERASI PT PUSRI
Daftar Isi:
- Association rules are used to identify frequent patterns and association structure among a set of database. Two statistical measures regulate association rule mining, they are support and confidence. This research aims to produce association rules' pattern which can be a reference for predict data's stock. Testing is done by input several values of support and confidence in the range from 0.001 until 0.007 and will be processed by FP-GROWTH algorithm. Relationships of goods or called Association Rule will be produced including their support, confidence and lift ratio value. The number of association rules that have been produced is influenced by supports' value, the biggest support's value is 0.02. On the other hand, in the combined test every month there were no significant differences in association rules that have been obtained.