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La Dodo
Universitas Esa Unggul
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Analysis of Tuberculosis Disease Case Growth From Medical Record Data, Viewed Through Clustering Algorithms (Case Study: Islamic Hospital Bogor) La Dodo; Nenden Siti Fatonah; Gerry Firmansyah; Habibullah Akbar
Jurnal Indonesia Sosial Sains Vol. 4 No. 09 (2023): Jurnal Indonesia Sosial Sains
Publisher : CV. Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59141/jiss.v4i09.884

Abstract

Tuberculosis is a chronic infectious disease caused by Mycobacterium tuberculosis infection. Tuberculosis can spread from one person to another through airborne transmission. This disease is most commonly found in the Asian region. Currently, Indonesia ranks second after India in terms of tuberculosis cases. The discovery of tuberculosis cases by province in Indonesia reveals that West Java Province is one of the contributors to the highest tuberculosis cases. It is known that the tuberculosis case rate in Bogor Regency is one of the highest in West Java. This serves as the foundation for the focus of this research, which will be conducted at Islamic Hospital Bogor, to determine the average age and gender of patients who are more susceptible to tuberculosis. One way to understand the growth of tuberculosis cases is through clustering using Data Mining Techniques, specifically several clustering algorithms such as k-means clustering, fuzzy c-means, and Gaussian mixture. These techniques aim to identify the growth of tuberculosis cases based on age range and gender. Therefore, the research results are expected to provide new insights, which could be valuable for decision-makers in various capacities, such as preventive measures, healthcare facility provision, and medication considerations.
Co-Authors Gerry Firmansyah Habibullah Akbar Nenden Siti Fatonah