Product Classification Based on Categories and CustomerInterests on the Shopee Marketplace Using the Naïve BayesMethod

Abstract

Marketplace is an electronic product marketing platform that
brings together many sellers and buyers to transact with
each other. The large variety of products sold on Shopee is
one of the reasons this application is in great demand by all
walks of life. However, the weakness of the large variety of
products sold in a marketplace causes buyers who have no
potential to buy these products. To overcome this problem, it
is necessary to do a classification to determine which
products are most in demand by customers. Product
categories consist of: Clothing, Beauty Products, Daily
Goods, Electronics, and Accessories. The classification
method used is Naïve Bayes and the software used is WEKA.
The next data collection is done by distributing
questionnaires to the existing customers on social media
namely, Whatsapp and Instagram, the distribution of the
questionnaire is conducted through Google form. There are
90 questionnaires that will be distributed in this study. Some
of the indicators asked in the questionnaire namely, do you
like shopping online? And what marketplaces are commonly
used. These results will be the training data. Interest
categories are divided into 4 categories, namely: Very
interested, Interested, Not interested, Very not interested. The
results obtained in this study are clothing products (72
respondents) are products that are in great demand, daily
goods products (7 respondents) are products of interest,
beauty and electronic products (5 respondents) are products
that are not in demand, and accessories (1 respondents ) is a
product that is not very attractive to customers on the Shopee
marketplace.