Analisis Clustering Pengelompokan Penjualan Paket Data Menggunakan Metode K-Means
At present with the COVID-19 pandemic situation that requires all activities based in the network, starting from work, college, school, everything is based on the network. Certain provider users will experience excessive data plan usage. This also has an effect on a counter that sells data packages, which must provide several data package services in accordance with current conditions. This research was conducted to analyze the grouping of sales of data packages that are often purchased by customers in a counter by using the K-Means method. The K-Means method is used because the K-Means algorithm is not influenced by the order of the objects used, this is proven when the writer tries to determine the initial cluster center randomly from one of the objects in the first calculation. sales of data packages at a counter. Variables used include Price, Active period, and number of data packages. The K-Means Cluster Analysis algorithm is basically applied to the problem of understanding consumer needs, identifying the types of data package products that are often purchased. The K-Means algorithm can be used to describe the characteristics of each group by summarizing a large number of objects so that it is easier.
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution-ShareAlike International License (CC-BY-SA 4.0) that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
Copyright without Restrictions
The journal allows the author(s) to hold the copyright without restrictions and will retain publishing rights without restrictions.
The submitted papers are assumed to contain no proprietary material unprotected by patent or patent application; responsibility for technical content and for protection of proprietary material rests solely with the author(s) and their organizations and is not the responsibility of the ULTIMATICS or its Editorial Staff. The main (first/corresponding) author is responsible for ensuring that the article has been seen and approved by all the other authors. It is the responsibility of the author to obtain all necessary copyright release permissions for the use of any copyrighted materials in the manuscript prior to the submission.