IMPLEMENTATION OF DATA MINING TO ANALYZE ONLINE SHOP SALES DATA WIMASK_ID

Yohanni Syahra, Firahmi Rizky, Hevlie Winda Nazry S, Rina Mahyuni, Putri Maharani Sebayang

Abstract


Wimask_id is a shop that sells various brands of skin care products and online souvenirs , the online shopping method that is currently popular with the public makes the sales data owned by online business actors increasingly piling up, including the Wimask_id online shop . The pile of data is unfortunate if it is not used as a source of information for the analysis process, but the problem is how the Wimask_id online shop can analyze the pile of data. To overcome this problem, the database in the form of sales data owned by the Wimask_id online shop can be analyzed, to obtain and explore consumer needs patterns through data mining information using the FP-Growth algorithm, to find a set of information that often arises in a large collection of information in optimizing product sales. In this study, the implementation of data mining using the FP-Growth algorithm is proposed. The results of this data mining analysis will help Wimask_id in determining the number and types of products that consumers are interested in, so that it can increase revenue and provide product offerings that suit consumer needs.

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DOI: https://doi.org/10.3059/insis.v0i0.22908

DOI (PDF): https://doi.org/10.3059/insis.v0i0.22908.g13147

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