M. ILHAM HABIBI, -
(2025)
APPLICATION OF DATA MINING FOR CERAMIC
SALES DATA ASSOCIATION USING APRIORI
ALGORITHM.
Application of Data Mining for Ceramic Sales Data Association Using Apriori Algorithm, 05 (02).
01-11.
ISSN 2796-7501
Abstract
This research is conducted to provide an understanding of consumer
purchasing patterns at CV. Sukses Bersama by applying data mining using
the association rules method and the Apriori algorithm to identify the
relationships between one item that influences other items within a ceramic
sales dataset at CV. Sukses Bersama. This information is expected to serve as
a foundation for improving sales strategies, optimizing customer
satisfaction, and expanding the company's market share. The Apriori
algorithm is a popular algorithm implemented to identify association rules
in data mining. The Apriori algorithm was chosen due to its ability to
efficiently identify association rules and its good scalability in handling large
datasets. This research begins with the collection of ceramic sales data,
followed by data preprocessing to clean and prepare the data. The Apriori
algorithm is then applied to discover the association rules, which generate
two matrices: support and confidence, and the results are subsequently
evaluated. This research was conducted using Google Colaboratory, a web
application that is a cloud-based platform provided by Google to run Python
code. The results of the study show that the Apriori algorithm can depict
significant association structures between different ceramic brand types in
the sales data of CV. Sukses Bersama. The calculation results show that the
rule has the maximum support and confidence value, namely 67% support
value and 84% confidence value in the rule "if you buy the DIAMD brand,
you will buy the TOTAL brand".
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