Article Per Year (5 Year)
p-Index From 2019 - 2024
0.408
P-Index
This Author published in this journals
All Journal Jurnal Riset Informatika
Samuel Samuel
Sekolah Tinggi Manajemen dan Ilmu Komputer Widuri
Computer Science & IT

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
SALES LEVEL ANALYSIS USING THE ASSOCIATION METHOD WITH THE APRIORI ALGORITHM Samuel Samuel; Asrul Sani; Agus Budiyantara; Merliani Ivone; Frieyadie Frieyadie
Jurnal Riset Informatika Vol 4 No 4 (2022): Period of September 2022
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1342.133 KB) | DOI: 10.34288/jri.v4i4.422

Abstract

The company does not yet know the pattern of consumer purchases because so far, the sales transaction data has not been used correctly and does not have a unique method to determine consumer buying patterns. To overcome the problems on the company, this research was done to reprocess sales transaction data for 2018-2019 using data mining techniques with association methods and apriori algorithms. RapidMiner is a supporting application used to find association rules derived from transaction data. Processed transaction data using the Knowledge Discovery in Database (KDD) approach. Thus, the company can determine consumer habits in buying goods derived from sales transaction data for 2018-2019. The results of this study are that in 2018, nine association rules were obtained, of which the best were CT G-246 ⇒ CT G-250 and CT G-250 ⇒ CT G-246. In 2019, nineteen association rules were obtained, of which the best were PN 0441, SK 0175 ⇒ SK 0530 and SK 0175, SK 0283 ⇒ SK 0530. From the best association rules, the goods in the Coat (imported), Pants, and Skirt categories are categories that are often bought together.
SALES LEVEL ANALYSIS USING THE ASSOCIATION METHOD WITH THE APRIORI ALGORITHM Samuel Samuel; Asrul Sani; Agus Budiyantara; Merliani Ivone S; Frieyadie Frieyadie
Jurnal Riset Informatika Vol. 4 No. 4 (2022): September 2022
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (822.013 KB) | DOI: 10.34288/jri.v4i4.194

Abstract

The company does not yet know the pattern of consumer purchases because, so far, the sales transaction data has not been used correctly and does not have a unique method to determine consumer buying patterns. The problems on the company, this research was done to reprocess sales transaction data for 2018-2019 using data mining techniques with association methods and apriori algorithms. RapidMiner is a supporting application to find association rules derived from transaction data. Processed transaction data using the Knowledge Discovery in Database approach. Thus, the company can determine consumer habits in buying goods from sales transaction data for 2018-2019. The results of this study are that in 2018, nine association rules were obtained, of which the best were CT G-246 ⇒ CT G-250 and CT G-250 ⇒ CT G-246. In 2019, nineteen association rules were received, of which the best were PN 0441, SK 0175 ⇒ SK 0530, and SK 0175, SK 0283, ⇒ SK 0530. From the best association rules, the goods in the Coat (imported), Pants, and Skirt categories are often bought together.
Co-Authors Agus Budiyantara Frieyadie Merliani Ivone Merliani Ivone S Sani, Asrul