Clustering History Data Penjualan Menggunakan Algoritma K-Means

  • Yogiswara Dharma Putra Department of Electrical and Computer Engineering, Post Graduate Program, Udayana University
  • Made Sudarma Magister Teknik Elektro Universitas Udayana, Gedung Pascasarjana Universitas Udayana
  • Ida Bagus Alit Swamardika Magister Teknik Elektro Universitas Udayana, Gedung Pascasarjana Universitas Udayana

Abstract

The company has a desire to develop an increase in its business so that it is not eroded by the very tight business competition. PT. Baliyoni Saguna is a company engaged in information technology and telecommunications which currently helps its customers to provide the best solutions according to customer needs. Product quality is a major factor in keeping customers alive and satisfied with the products provided by PT. Baliyoni Saguna. These products need to be reviewed in order to have a reference in creating the best products. Clustering is a method that can be used to see the level of sales that have been made based on the formed clusters. The K-Means algorithm is a method capable of processing sales history data owned by PT. Baliyoni Saguna in forming groups according to the item category of the item. The K-Means algorithm is able to provide convenience in processing large data so that it can be processed more quickly and efficiently. The results of the application of the K-Means algorithm formed 3 clusters representing the most desirable, least desirable, and least desirable categories. In the most desirable category there are 5 total items, 4 in the interested category there are 4 total items, and 14 items less desirable. These results are expected to help in creating quality goods so as to maintain product quality and customer satisfaction.


 


Keywords – Clustering, K-Means Algorithm, PT. Baliyoni Saguna

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References

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Published
2021-12-25
How to Cite
DHARMA PUTRA, Yogiswara; SUDARMA, Made; SWAMARDIKA, Ida Bagus Alit. Clustering History Data Penjualan Menggunakan Algoritma K-Means. Majalah Ilmiah Teknologi Elektro, [S.l.], v. 20, n. 2, p. 195-202, dec. 2021. ISSN 2503-2372. Available at: <https://ojs.unud.ac.id/index.php/JTE/article/view/71534>. Date accessed: 27 june 2022. doi: https://doi.org/10.24843/MITE.2021.v20i02.P03.