IMPLEMENTASI ALGORITMA K-NEAREST NEIGHBOR PADA WEBSITE REKOMENDASI LAPTOP

Chandra Arief Rahardja, Try Juardi, Halim Agung
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引用次数: 4

Abstract

There are various types of laptops that make consumers or prospective buyers have difficulty in making choices accurately and precisely. The K-Nearest Neighbor (K-NN) algorithm was chosen because the K-NN algorithm is a form of model that can help classify data based on the closest distance. This system is designed to help prospective buyers in choosing a laptop based on purchase objectives such as gaming, design, and office, price, also specifications regarding the desired laptop. This system helps provide a shadow or reference to users or prospective buyers in determining the selection of laptops as needed. Based on user satisfaction test, from testing carried out to 10 users. As a result, 8 out of 10 people answered with the answers agreeing with the results of the recommendations given, with the results of the percentage of satisfaction with the recommendations of 80%, therefore the recommendations of laptops made were declared successful
实现算法k -最近邻pagada网站推荐笔记本电脑
各式各样的笔记本电脑让消费者或潜在买家很难准确、准确地做出选择。选择k -最近邻(K-NN)算法是因为K-NN算法是一种模型形式,可以帮助根据最近距离对数据进行分类。该系统旨在帮助潜在买家根据购买目标(如游戏、设计和办公)、价格以及所需笔记本电脑的规格来选择笔记本电脑。该系统有助于为用户或潜在买家在决定笔记本电脑的选择时提供一个影子或参考。基于用户满意度测试,从测试进行到10个用户。结果,10个人中有8个人回答的答案同意所给出的建议的结果,结果对建议的满意率为80%,因此笔记本电脑的推荐被宣布为成功
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