K-MEANS CLUSTERING ALGORITHM FOR SERVICE DATA ANALYSIS BASED ON CUSTOMERS COMBINATION

Zulhendra Zulhendra, G. W. Nurcahyo, Julius Santony
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Abstract

In this study using Data Mining, namely K-Means Clustering. Data Mining can be used in searching for a large enough data analysis that aims to enable Indocomputer to know and classify service data based on customer complaints using Weka Software. In this study using the algorithm K-Means Clustering to predict or classify complaints about hardware damage on Payakumbuh Indocomputer. And can find out the data of Laptop brands most do service on Indocomputer Payakumbuh as one of the recommendations to consumers for the selection of Laptops.
基于客户组合的业务数据分析K-means聚类算法
在本研究中使用数据挖掘,即k均值聚类。数据挖掘可以用于搜索足够大的数据分析,目的是使Indocomputer能够使用Weka Software了解和分类基于客户投诉的服务数据。本研究使用K-Means聚类算法对Payakumbuh Indocomputer的硬件损坏投诉进行预测或分类。并且可以在Indocomputer Payakumbuh上找到大多数笔记本电脑品牌的数据,作为消费者选择笔记本电脑的建议之一。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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