Article Per Year (5 Year)
p-Index From 2020 - 2025
0.23
P-Index
This Author published in this journals
All Journal Jurnal Multidisiplin Dehasen (MUDE)
Anton Saputra
Universitas Dehasen Bengkulu
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Astronomy Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Neuroscience Nursing Physics Public Health Social Sciences Transportation Veterinary Other

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
Implementasi Metode Association Rule Mining Pada Penjualan Barang Di Toko Bangunan Ada Mas Menggunakan Algoritma Apriori Anton Saputra; Herlina Latipa Sari; Devi Sartika
Jurnal Multidisiplin Dehasen (MUDE) Vol 2 No 4 (2023): Oktober
Publisher : Universitas Dehasen Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37676/mude.v2i4.4805

Abstract

The purpose of this research is to implement the association rule mining method on sales transaction data at the store and also to find out the most popular and most sold building materials at the Ada Mas Building Shop. The implementation of the Association Rule Mining Method on the sale of goods at the Ada Mas Building Shop is used to provide information on the results of the sales pattern of building materials every month which can be used as a parameter in managing the inventory of building materials at the Ada Mas Building Shop, besides that it can provide information on the most popular and most sold building materials at the Ada Mas Building Shop. Based on sales transaction data for September 2022 as many as 193 transactions, the results of 2 itemset sales patterns using the Association Rule Mining Method that meet the minimum support of 10% and minimum confidence of 50% are the most popular items, namely Iron 10 KSTY, Iron 8 KSTY, and Iron 6 KSTY.
Co-Authors Devi Sartika Herlina Latipa Sari