  The growth of internet users in Indonesia gives an impact on many aspects of
daily life, including commerce. Indonesian small-medium enterprises took this
advantage of new media to derive their activity by the meaning of online
commerce. Until now, there is no known practical implementation of how to
predict their sales and revenue using their historical transaction. In this
paper, we build a sales prediction model on the Indonesian footwear industry
using real-life data crawled on Tokopedia, one of the biggest e-commerce
providers in Indonesia. Data mining is a discipline that can be used to gather
information by processing the data. By using the method of classification in
data mining, this research will describe patterns of the market and predict the
potential of the region in the national market commodities. Our approach is
based on the classification decision tree. We managed to determine predicted
the number of items sold by the viewers, price, and type of shoes.
