• Fauzia Allamatul Fithri (1*) Universitas Mercu Buana
  • Sukma Wardhana (2) Universitas Mercu Buana

  • (*) Corresponding Author
Keywords: cluster validation, data mining, davies bouldin index, k-means clustering, sales


Data mining is a process to obtain useful information from a database warehouse in the form of knowledge. Data transaction history of sales can be information for a business decision. Toko Usaha Mandiri has a problem with the stock of goods, and there are passive goods that settle in the warehouse for a relatively long period. Previous research conducted data analysis to form data clustering into useful information. This study aims to analyze sales data by applying the K-Means Clustering algorithm to form sales clusters. The results of data clustering form cluster1, cluster2 and cluster3 with percentage values of 62% (11 data), 8% (56 data) and 30% (25 data), respectively. Cluster validation of K-Means Clustering algorithm with Davies Bouldin Index produces a value of 0.2. The information of sales clustering can be an alternative solution, input for stock management and marketing strategies.


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Adiya, M. H., & Desnelita, Y. (2019). National Journal of Technology and Information Systems Application of K-Means Algorithm For Clustering Drug Data at Pekanbaru Hospital. National Technology and Information Systems, 01, 17–24.

Butsianto, S., & Saepudin, N. (2020). Application of Data Mining To Students' Interest in Mathematics Subjects With K-Means Method. National Journal of Computing and Information Technology (JNKTI), 3(1), 51–59.

Fithri, F. A., & Wardhana, S. (2021). Cluster Analysis Of Sales Transaction Data Using K-Means Clustering At Toko Usaha Mandiri. 17(2), 1–7.

Handoko, K. (2018). Grouping Mining Data on The Number of Passengers at Hang Nadim Airport. Computer-Based Information System Journal, 6(2), 60.

Hutabarat, S.M., & Sindar, A. (2019). Data Mining Of Motorcycle Parts Sales Using K-Means Algorithm. National Journal of Computing and Information Technology (JNKTI), 2(2), 126.

Indriyani, F., & Irfiani, E. (2019). Clustering Sales Data at Outdoor Supply Stores Using the K-Means Method. JUITA: Journal of Informatics, 7(2), 109.

Noviyanto. (2020). Application of Data Mining in Grouping The Number of Deaths. Paradigm-Journal of Informatics and Computers, 22(2).

Rofiqo, N., Windarto, A. P., & Hartama, D. (2018). Application of Clustering in Residents Who Have Health Complaints With K-Means Datamining. KOMIK (National Conference on Information and Computer Technology), 2(1), 216–223.

Setiawan, S. (2018). Utilization of K-Means Method in Determining Inventory of Goods. PIXELS: Research in Computer Science embedded systems and logic, 6(1), 41–48.

Sibuea, M. L., & Safta, A. (2017). Mapping Outstanding Students Using the K-Means Clustering Method. Jurteksi, 4(1), 85–92.

Siregar, M. H. (2018). Data Mining Clustering of Building Tools Using K-Means Method (Case Study In Adi Building Store). Journal of Technology and Open Source, 1(2), 83–91.

Sukamto, S., Id, I. D., & Angraini, T. R. (2018). Determination of Fire-Prone Areas in Riau Province Using Clustering K-Means Algorithm. JUITA: Journal of Informatics, 6(2), 137.

Syahidatul Helma, S., Rustiyan, R. R., Normala, E., Information Systems Studies Faculty of Science and Technology, P., State Islam Sultan Syarif Kasim Riau, U., Soebrantas No, J., & Baru, S. (2019). Clustering on Pekanbaru City Health Care Facility Data Using K-Means Algorithm. Puzzle Research Data Technology (Predatech) Faculty of Science and Technology, 1(November), 4.

Triyansyah, D., & Fitrianah, D. (2018). Data Mining Analysis Uses K-Means Clustering Algorithms to Determine Marketing Strategies. Journal of Telecommunications and Computers, 8(3), 163.

Yaumi, A. S., Zulfiqkar, Z., & Nugroho, A. (2020). Clustering of Consumer Characters Against Product Selection Tendencies Using K-Means. JOINTECS (Journal of Information Technology and Computer Science), 5(3), 195.

Yunita. (2018). Application of Data Mining Uses K-Means Clustering Algorithm on Admission of New Students (Case Study: Indragiri Islamic University). Journal of Systemization, 7(September), 238–249.

How to Cite
Fithri, F., & Wardhana, S. (2021). The CLUSTER ANALYSIS OF SALES TRANSACTION DATA USING K-MEANS CLUSTERING AT TOKO USAHA MANDIRI. Jurnal Pilar Nusa Mandiri, 17(2), 113-118.
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