Analysis of Customer Satisfaction with the Application of Data Mining Using the K-Means Clustering Method in CV. Green Publisher Indonesia

customer satisfaction data mining k-means clustering method

Authors

  • Dwi Febri Syawaludin
    febrisyawaludin445@gmail.com
    Faculty of Information Technology, Universitas Catur Insan Cendekia, Indonesia , Indonesia
  • Muhammad Hatta Faculty of Information Technology, Universitas Catur Insan Cendekia, Indonesia , Indonesia
  • Kusnadi Faculty of Information Technology, Universitas Catur Insan Cendekia, Indonesia , Indonesia
January 20, 2025

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In this digital era, data has become one of the most valuable assets for all companies. Data mining is a method that can be used to explore knowledge. The current research aims to analyze CV customer satisfaction. Green Publisher Indonesia by applying data mining techniques using the k-means clustering method. In this research, data will be collected regarding customer preferences and levels of satisfaction through sources such as online surveys. The data will be analyzed into the rapidminer 5.3 system using the k-means clustering algorithm. The research material used is customer data that has been obtained within a certain period by providing an Online Questionnaire (Google Form). In this research, researchers used one of the methods in Data Mining, namely the K-Means Clustering method. The results of the clustering execution using K-Means Clustering were 163 data resulting in 2 clusters with details of cluster 0 as 131 data or 80.36% and cluster 1 as 32 data or 19.64%.  The results of the analysis show that there is a significant difference in the level of satisfaction between the two clusters.