PENERAPAN ALGORITMA APRIORI UNTUK MENCARI POLA PENJUALAN PRODUK HERBAL
(STUDI KASUS: TOKO HANAWAN GEMILANG)
Total View This Week0
Total View This Week0
Institusion
Universitas Pembangunan Nasional Veteran Jakarta
Author
Pratama Haryandi, .
Subject
QA75 Electronic computers. Computer science
Datestamp
2021-12-21 07:38:12
Abstract :
Herbal products are products derived from medicinal plants. Herbal products are included in a variety of products such as supplements, vitamins or herbal medicines. Hanawan Gemilang store is one of the herbal product sellers in Jakarta. At the store there is no combination pattern of selling herbal products to increase sales. This study will look for patterns with association rules related to sales transaction data, namely support and confidence values. The data used is sales transaction data of 30 types of herbal products. The data mining technique used is the association rule with the Apriori method, which aims to generate association rules. After all high-frequency patterns are found, then we look for association rules that meet the minimum requirements for the confidence of association rules so as to produce rules between combinations of herbal products. After being tested several times on the data, the Minimum Support and Minimum Confidence values taken are 10% and 58%. With the Minimum Support value, the Minimum Confidence taken produces 5 eligible association rules and the largest Confidence value is 71% in the rules, if you buy White Turmeric and Bilberry Carrot then buy Garlic.
Herbal products are products derived from medicinal plants. Herbal products are included in a variety of products such as supplements, vitamins or herbal medicines. Hanawan Gemilang store is one of the herbal product sellers in Jakarta. At the store there is no combination pattern of selling herbal products to increase sales. This study will look for patterns with association rules related to sales transaction data, namely support and confidence values. The data used is sales transaction data of 30 types of herbal products. The data mining technique used is the association rule with the Apriori method, which aims to generate association rules. After all high-frequency patterns are found, then we look for association rules that meet the minimum requirements for the confidence of association rules so as to produce rules between combinations of herbal products. After being tested several times on the data, the Minimum Support and Minimum Confidence values taken are 10% and 58%. With the Minimum Support value, the Minimum Confidence taken produces 5 eligible association rules and the largest Confidence value is 71% in the rules, if you buy White Turmeric and Bilberry Carrot then buy Garlic.
Download
book
BibTex
Latex, Jabref
cloud_download
Original Resource
url resource Institution
