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All Journal JURNAL MEDIA INFORMATIKA BUDIDARMA
Ni Kadek Bumi Krismentari
STMIK STIKOM Indonesia, Denpasar
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering

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Penerapan Apriori Hybrid Pada Transaksi Penjualan Barang I Made Dwi Putra Asana; Ni Luh Wiwik Sri Rahayu Ginantra; Wayan Gede Suka Parwita; Ni Kadek Bumi Krismentari; Ni Putu Suci Meinarni
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 5, No 4 (2021): Oktober 2021
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v5i4.3350

Abstract

Ayu Nadi Swalayan is a retail company that produces a lot of every day sales transaction data, and it is stored for years without knowing the benefits and the placement of the goods is still random. From these problems, an effort is needed to process the data so the data is useful in the future. One of the process is using data mining techniques with apriori hybrid algorithm to find association rules for an items combination. Data product sale in a certain period is used to find the association rules. The results of this study are the development of applications that are used to determine consumer spending habits. So that the company can develop a strategy to promote the product sale and close placement for items that are often purchased together. The application testing found the effect of minimum support, minimum confidence on the number of rules, and lift ratio testing. The smaller the minimum support and minimum confidence, the more rules are generated and vice versa. The lift ratio value is directly proportional to the minimum confidence value and inversely proportional to the minimum support value. The higher the minimum confidence value, the higher the lift ratio value and vice versa. The more items in the transaction cause the minimum support threshold to be lowered in order to generate rules for the data analysis process with the hybrid apriori algorithm
Co-Authors Asana, I Made Dwi Putra Ni Luh Wiwik Sri Rahayu Ginantra Ni Putu Suci Meinarni Wayan Gede Suka Parwita