Enhancement of hepatitis virus outcome predictions with application of K-means clustering

G. Kurniawan, Z. Rustam

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Hepatitis is an inflammation of the liver. There are five types of hepatitis virus. Meanwhile, hepatitis B and hepatitis C virus can progress into liver cancer. Someone that is suspected to have hepatitis, can do a laboratory research to gain information about their condition. The data and information from the laboratory could be used to build a program which will predict the outcome for new data with similar symptoms of hepatitis B and hepatitis C. In this paper, the outcome of this problem was predicted using K-Means Clustering method based on the early information or data from hospital's laboratory. K-Means Clustering was a clustering method which provide 84.85 % accurate prediction for new data with similar symptoms with hepatitis B and hepatitis C. This method will decide whether a new data with similar symptoms to hepatitis B and hepatitis C will be classified as hepatitis B or C. Thus, new data and information about their health condition considering to hepatitis B and hepatitis C could be effectively presumed.

Original languageEnglish
Title of host publicationProceedings of the 4th International Symposium on Current Progress in Mathematics and Sciences, ISCPMS 2018
EditorsTerry Mart, Djoko Triyono, Ivandini T. Anggraningrum
PublisherAmerican Institute of Physics Inc.
ISBN (Electronic)9780735419155
DOIs
Publication statusPublished - 4 Nov 2019
Event4th International Symposium on Current Progress in Mathematics and Sciences 2018, ISCPMS 2018 - Depok, Indonesia
Duration: 30 Oct 201831 Oct 2018

Publication series

NameAIP Conference Proceedings
Volume2168
ISSN (Print)0094-243X
ISSN (Electronic)1551-7616

Conference

Conference4th International Symposium on Current Progress in Mathematics and Sciences 2018, ISCPMS 2018
CountryIndonesia
CityDepok
Period30/10/1831/10/18

Keywords

  • Hepatitis
  • k-means clustering
  • liver cancer

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  • Cite this

    Kurniawan, G., & Rustam, Z. (2019). Enhancement of hepatitis virus outcome predictions with application of K-means clustering. In T. Mart, D. Triyono, & I. T. Anggraningrum (Eds.), Proceedings of the 4th International Symposium on Current Progress in Mathematics and Sciences, ISCPMS 2018 [020044] (AIP Conference Proceedings; Vol. 2168). American Institute of Physics Inc.. https://doi.org/10.1063/1.5132471