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

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Date

March 4, 2021

Language
Identifiers
  • handle:  10670/1.p69kc2
  • The 6th Seminar & Conference on Business & Technology in ICT Industry, 2015
Collection

arXiv

Organization

Cornell University


Keywords

Economics - General Economics Computer Science - Computers and Society


Cite this document

Raden Johannes et al., « Sales Prediction Model Using Classification Decision Tree Approach For Small Medium Enterprise Based on Indonesian E-Commerce Data », arXiv, ID : 10670/1.p69kc2


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Abstract 0

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.

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