The competitive nature of the business world demands every business owner to
carry out their sales activities more effectively and efficiently. Sales or marketing
activities require a fundamental sales strategy concept that aligns with the
business's interests and customers' needs and desires. All sales activities
undertaken by a company are meant to provide customer satisfaction, aiming to
achieve optimal profits. The sales objective can be achieved if the planned sales
activities are executed as intended. Therefore, companies must implement
appropriate sales strategies that suit their market conditions to attract customers
to make purchases, especially in categorizing product sales levels. There is a need
to boost sales, which can be achieved through data mining to categorize product
sales levels using the K-Means Clustering method. Categorizing product sales
levels using the K-Means Clustering method was selected because this method was
considered adequate and quick in data processing, providing optimal and quality
results based on previous sales history. The K-Means method was one of the most
commonly used forms of data analysis because it was relatively easy to understand
and implement. The K-Means Clustering method was appropriate for this project
as it involved hundreds of data points and required high accuracy in object
measurement. The results of this project assisted the store owner in categorizing
product inventory based on sales levels, ranging from very popular, popular, to less
popular. This categorization aided in managing products for subsequent periods,
including improving the quality of products with low sales volume and maintaining
the quality of products with high sales volume.