基于印度尼西亚电子商务数据的中小企业分类决策树销售预测模型
Sales Prediction Model Using Classification Decision Tree Approach For Small Medium Enterprise Based on Indonesian E-Commerce Data
摘要：
印度尼西亚互联网用户的增长对日常生活的许多方面产生了影响，包括商业。印尼的中小企业利用新媒体的优势，以在线商务的意义来衍生他们的活动。到目前为止，还没有已知的实际实现如何使用他们的历史交易来预测他们的销售和收入。在本文中，我们使用印度尼西亚最大的电子商务提供商之一Tokopedia上抓取的真实数据建立了印度尼西亚鞋类行业的销售预测模型。数据挖掘是一门通过处理数据来收集信息的学科。利用数据挖掘中的分类方法，描述市场的模式，预测该地区在全国市场商品中的潜力。我们的方法是基于分类决策树。我们设法确定预测的数量的项目出售的观众，价格和类型的鞋。
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
