Jurnal Teknik Informatika (JUTIF)
Vol. 4 No. 5 (2023): JUTIF Volume 4, Number 5, October 2023

COMPARISON OF DATA MINING ALGORITHM FOR CLUSTERING PATIENT DATA HUMAN INFECTIOUS DISEASES

Nurfadilla, Nadia (Unknown)
Afdal, M. (Unknown)
Permana, Inggih (Unknown)
Zarnelly, Zarnelly (Unknown)



Article Info

Publish Date
05 Oct 2023

Abstract

Tuberculosis is known as an infectious disease whose transmission through air intermediaries is caused by the germ Mycobacterium Tuberculosis. This disease has become a case that has almost spread throughout the pelalawan Regency with the number continuing to increase every year so that it is possible to be able to group the areas where this disease spreads. Grouping of tuberculosis data distribution areas using data mining methods in the form of clustering with the data used coming from the Pelalawan Regency Health Office from 2020 to 2022. The data obtained earlier will then be processed using k-medoids, k-means, and x-means algorithms. The beginning of this research was by processing data from each year using these three algorithms. Determination of the most optimal algorithm using DBI or known as the Davies Bouldin Index. The results of the processing of existing indicators are grouped into three sections, namely areas with a high, medium, and low number of cases. From the results of the study, the optimal algorithm in 2020 data is the k-medoids algorithms with a DBI value of 0,553 and in 2021 data, the most optimal algorithm is the k-means and x-means algorithm with similar DBI values of 0,582. Furthermore, the data in 2022 the most optimal algorithms are the k-means and x-means algorithms because they have the same DBI value, which is 0,510.

Copyrights © 2023






Journal Info

Abbrev

jurnal

Publisher

Subject

Computer Science & IT

Description

Jurnal Teknik Informatika (JUTIF) is an Indonesian national journal, publishes high-quality research papers in the broad field of Informatics, Information Systems and Computer Science, which encompasses software engineering, information system development, computer systems, computer network, ...