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Searching Cheapest Product on Three Different E-Commerce Using K-Means Algorithm

机译:使用K-Means算法在三种不同的电子商务上搜索最便宜的产品

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The development of e-commerce is starting to change people's lifestyles, not least the people of Indonesia. The existence of e-commerce is very helpful user in buying and selling products. There are many e-commerce that can be found today. Some of the famous e-commerce in Indonesia are Bukalapak, Lazada, and Blibli. A large number of existing e-commerce makes users, especially buyers, have difficulty when looking for products at the cheapest price. This happens because each e-commerce offers different prices for the same product. This research aims to make the cheapest product search system in Bukalapak, Lazada, and Blibli using K-Means algorithm. The results of experiments showed that K-Means algorithm can be used to classify product data from Bukalapak, Lazada, and Blibli well. The results of the clustering process can also help for searching the cheapest products from the three e-commerce becomes faster. However, the number of clusters used will affect the effectiveness of the search process on the system.
机译:电子商务的发展正在开始改变人们的生活方式,尤其是印度尼西亚人民。电子商务的存在对用户买卖产品非常有帮助。今天可以找到许多电子商务。印度尼西亚有一些著名的电子商务,包括Bukalapak,Lazada和Blibli。大量现有的电子商务使用户(尤其是购买者)在以最便宜的价格寻找产品时遇到困难。发生这种情况是因为每个电子商务为同一产品提供不同的价格。这项研究旨在使用K-Means算法制作Bukalapak,Lazada和Blibli中最便宜的产品搜索系统。实验结果表明,K-Means算法可以很好地对来自Bukalapak,Lazada和Blibli的产品数据进行分类。聚类过程的结果还可以帮助从三个电子商务中搜索最便宜的商品变得更快。但是,使用的群集数量将影响系统上搜索过程的有效性。

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