Challenging Analytic Data Opportunities in Smart Health with Algorithm (Study Case: Bumi Medika Ganesha ITB)

  • Aristyo Hadikusuma Telkom University
  • Anung Asmoro Telkom Indonesia
  • Joko Rurianto Telkomsel, Indonesia
Abstract views: 89 , 714 downloads: 51
Keywords: component, k-mean


Weka is a tool to help the data science to clustering data. Weka has feature K-means which help clustering data to spesific analysis. Clustering analysis is a technique for categorizing and dividing objects into groups. Each object has certain characteristics. Because the data has a lot of variety and quantity,By using this K-Means algorithm the patient temperature data already obtained will be grouped into several clusters. Grouping of data by clustering is expected to be a strategy for decision making.


Download data is not yet available.


[1] G. Eason, B. Noble, and I.N. Sneddon, “On certain integrals of
[2] Lipschitz-Hankel type involving products of Bessel functions,” Phil. Trans. Roy. Soc. London, vol. A247, pp. 529-551, April 1955. (references)
[3] J. Clerk Maxwell, A Treatise on Electricity and Magnetism, 3rd ed., vol.
2. Oxford: Clarendon, 1892, pp.68-73.
[4] I.S. Jacobs and C.P. Bean, “Fine particles, thin films and exchange anisotropy,” in Magnetism, vol. III, G.T. Rado and H. Suhl, Eds. New York: Academic, 1963, pp. 271-350.
[5] K. Elissa, “Title of paper if known,” unpublished.
[6] R. Nicole, “Title of paper with only first word capitalized,” J. Name Stand. Abbrev., in press.
[7] Y. Yorozu, M. Hirano, K. Oka, and Y. Tagawa, “Electron spectroscopy studies on magneto-optical media and plastic substrate interface,” IEEE Transl. J. Magn. Japan, vol. 2, pp. 740-741, August 1987 [Digests 9th Annual Conf. Magnetics Japan, p. 301, 1982].
[8] M. Young, The Technical Writer’s Handbook. Mill Valley, CA: University Science, 1989.
[9] M. Maila and J. Shi, “A random walks view of spectral segmentation,” in AI and STATISTICS (AISTATS) 2001, 2001
[10] M. Cocco and A. Tuzzi, “New data collection modes for surveys: A comparative analysis of the influence of survey mode on question- wording effects,” Qual. Quant., vol. 47, no. 6, pp. 3135–3152, 2013
[11] Zhang G.P 2001. Time Series Forecasting Using a hybrid ARIMA and Neural Network Model,
[12] Night, John F. Jantung Kuat Bernafas Lega.Bandung:Indonesia Publishing House, 1995
[13] Handoyo, R. 2013. Perbandingan Metode Clustering Menggunakan

Metode Single Linkage dan K-Means pada Pengelompokan Dokumen.
Proposal Tugas Akhir Institut Teknologi Telkom. Bandung
[14] [6] Bholowalia, Kumar., (2014). A Clustering Techniques based on Elbow Method and K-means in WSN. International Journal of Computer Application (0975 - 8887)

[15] [7] Hung, C.M., Wu, J., Chang, J.H. & Yang, D.L., 2005. An Efficient k-Means Clustering Algorithm Using Simple Partitioning. Journal of Information Science and Engineering, XXI(1), pp.1157-77
[16] Ediyanto,, 2013. Pengklasifikasian Karakteristik Dengan Metode K-Means Cluster Analysis. Buletin Ilmiah Mat. Stat. Dan Terapannya (Bimaster), II(2), pp. 133-136

[17] Nuha, H., Liu, B., Mohandes, M., Balghonaim, A., & Fekri, F. (2021). Seismic data modeling and compression using particle swarm optimization. Arabian Journal of Geosciences, 14, 1-11.
How to Cite
Hadikusuma, A., Asmoro, A., & Rurianto, J. (2023). Challenging Analytic Data Opportunities in Smart Health with Algorithm (Study Case: Bumi Medika Ganesha ITB). Indonesia Journal on Computing (Indo-JC), 8(2), 1-7.
Computational and Simulation