Implementasi Metode Clustering DBSCAN pada Proses Pengambilan Keputusan

  • Anindya Santika Devi Jurusan Teknologi Informasi, Universitas Udayana
  • I Ketut Gede Darma Putra Universitas Udayana
  • I Made Sukarsa Universitas Udayana

Abstract

Spatial Data Clustering is one of the significant techniques in data mining which used to obtain information or knowledge in a large number of spatial data from various applications. One technique that being a pioneer in the development of spatial data clustering algorithm is DBSCAN. This study is focused on implementation of DBSCAN method in decision making process in order to help a company to decide its potential customer. The trial results in this study show that DBSCAN method has been successfully conduct clustering process to support decision making process in determination of potential customer by forming several number of clusters.

Downloads

Download data is not yet available.

References

[1] Fayyad U, Piatetsky-Shapiro G, and Smyth P, “Knowledge Discovery and Data Mining: Towards a Unifying Framework,” in Proceedings of the 2nd Int. Conference on Knowledge Discovery and Data Mining. Portland, 1996, pp. 82–88.
[2] Shekhar S, Zhang P, Huang Y, and Vatsavai RR, “Trends in spatial data mining. Data mining: Next generation challenges and future directions,” pp. 357–380, 2003.
[3] Matheus CJ, Chan PK, and Piatetsky-Shapiro G, “Systems for Knowledge Discovery in Databases,” IEEE Trans. Knowl. Data Eng., vol. 5, no. 6, pp. 903–913, 1993.
[4] Mumtaz K, “An Analysis on Density Based Clustering of Multi Dimensional Spatial Data,” Indian Journal of Computer Science and Engineering (IJCSE), vol. 1, no. 1, pp. 8–12, 2010.
[5] Zakrzewska D and Murlewski J, “Clustering Algorithms for Bank Customer Segmentation,” in Proceedings of 5th Int. Conference on Intelligent Systems Design and Applications, Poland, 2005, pp. 197–202.
[6] H. Xiaohui, “A New Customer Segmentation Framewok Based on Biclustering Analysis,” J. Softw., vol. 9, no. 6, pp. 1359–1366, 2014.
[7] P. Tan, Introduction to Data Mining. Boston: Pearson Education, 2006.
Published
2015-12-01
How to Cite
DEVI, Anindya Santika; PUTRA, I Ketut Gede Darma; SUKARSA, I Made. Implementasi Metode Clustering DBSCAN pada Proses Pengambilan Keputusan. Lontar Komputer : Jurnal Ilmiah Teknologi Informasi, [S.l.], p. 185-191, dec. 2015. ISSN 2541-5832. Available at: <https://ojs.unud.ac.id/index.php/lontar/article/view/32454>. Date accessed: 21 nov. 2024. doi: https://doi.org/10.24843/LKJITI.2015.v06.i03.p05.
Section
Articles

Most read articles by the same author(s)

<< < 1 2 3 > >>