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

Sales Prediction Model Using Classification Decision Tree Approach For Small Medium Enterprise Based on Indonesian E-Commerce Data