Article Sidebar

Submitted
July 15, 2021
Accepted
September 4, 2021
Published
September 15, 2021
Download
PDF
Statistic
Read Counter : 469 Download : 607

Main Article Content

Abstract

Through increasing the use of contraceptives to limit births, the Family Planning (KB) Program is one of the government's efforts to control the rate of population growth. Klaten Districts is one of the regencies in Central Java Province with a relatively high number of births and relatively low coverage of active family planning. This study aimed to determine the grouping of sub-districts and these characteristics in the Klaten Districts in 2020. The method used in this study was a hierarchical cluster analysis method, with the best method being the centroid method. In this study obtained 3 clusters with cluster 1 consisting of 23 sub-districts, cluster 2 consists of 2 sub-districts and cluster 3 with 1 sub-district. The cluster characteristics based on the highest number of users of contraceptive methods are cluster 1-contraceptives injection, cluster 2- contraception implant, and IUDs in cluster 3

Keywords

Contraceptive methods Hierarchical clustering Centroid method Characteristics of cluster

Article Details

How to Cite
Utari, D. T., & Hanun, D. S. (2021). Hierarchical Clustering Approach for Region Analysis of Contraceptive Users. EKSAKTA: Journal of Sciences and Data Analysis, 2(2), 99–108. https://doi.org/10.20885/EKSAKTA.vol2.iss2.art3
Download Citation
Endnote/Zotero/Mendeley (RIS)
BibTeX
Crossref
Scopus
Google Scholar
Europe PMC

References

  1. A. Sulistyawati, Pelayanan Keluarga Berencana, Salemba Medika, Jakarta, 2011.
  2. S. L. Naustion, Faktor-Faktor Yang Mempengaruhi Penggunaan MKJP di Enam Wilayah Indonesia, Pusat Penelitian dan Pengembangan KB, Jakarta, 2011.
  3. B. K. RI, Riset Kesehatan Dasar (RISKESDAS), Balitbang Kemenkes RI, Jakarta, 2013.
  4. P. Shetty and S. Singh, Hierarchical Clustering: A Survey, International Journal of Applied Research 7(4) (2021) 178-181.
  5. NHS, Your Contraception Guide, 17 March 2021. [Online]. Available: https://www.nhs.uk/conditions/contraception/. [Accessed 7 June 2021].
  6. P. N. Tan, M. Steinbach and V. Kumar, Introduction to Data Mining, Pearson Education, Boston, 2006.
  7. J. F. Hair, R. E. Anderson, R. L. Tatham and W. C. Black, Multivariate Data Analysis Fifth Edition, Prentice-Hall, Inc., USA, 1998.
  8. R. A. Johnson and G. K. Bhattacharyya, Statistics Principles & Methods, John Wiley & Sons, USA, 2010.
  9. J. I. Daoud, Multicollinearity and Regression Analysis, Journal of Physics: Conference Series 949 (2017) 1-6.
  10. S. Saracli, N. Dogan and I. Dogan, Comparison of Hierarchical Cluster Analysis Methods by Cophenetic Correlation, Journal of Inequalities and Applications 203(1) (2013) 1-8.
  11. P. Kaur, J. Stoltzfus and V. Yellapu, Descriptive Statistics, International Journal of Academic Medicine 4(1) (2018) 60-63.
  12. N. W. D. Ayuni and I. G. A. M. K. K. Sari, Analysis of Factors that Influencing the Interest of Bali State Polytechnic’s Students in Entrepreneurship, Journal of Physics: Conference Series, 953 (2018) 1-10.
  13. I. Gozhali, Aplikasi Analisis Multivariat dengan Program SPSS, Badan Penerbit Universitas Diponegoro, Semarang, 2001.
  14. P. R. Carvalho, C. S. Munita, A. L. Lapolli, Validity Studies Among Hierarchical Methods of Cluster Analysis Using Cophenetic Correlation Coefficient, International Nuclear Atlantic Conference, (C) (2017)
  15. Z. Zhang, F. Murtagh, S. P. Poucke, S. Lin and P. Lan, Hierarchical Cluster Analysis in Clinical Research with Heterogeneous Study Population: Highlighting Its Visualization With R, Annals of Translational Medicine 5(4) (2017) 1-11.