Analisis Clustering Paket Data Internet di Indonesia Menggunakan Metode K-Means
Abstract
Disruption of technology and the impact of the recent pandemic has made people access the internet longer than before, especially with smartphones. Before accessing the internet, users must purchase a data package provided by an internet service provider. Various data packages are provided by internet service providers. Starting from network coverage, speed, number of quotas, active period, to tariffs are the choices of each operator. These various offerings often make users confused because they have to adjust to economic conditions. The existence of knowledge analysis in the database, grouping data packets can be done using the k-means method. K-means groups data by iterating and creating groups based on the closest distance of the data to the center point. K-means is very widely used because of its simplicity. Before clustering, the data will go through a preprocessing process. The end result is four clusters that have their own characteristics. For example, cluster four has the characteristics of a small quota with a long active period, which is suitable for the typical community who only wants to stay connected to the internet for communication.
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