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All Journal Jurnal ilmiah teknologi informasi Asia
Faqih, Luthfi Ramdhan
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Computer Science & IT

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Analisis Klasterisasi Penyakit Malaria Menggunakan Metode K-Means di Indonesia Faqih, Luthfi Ramdhan; Riska, Suastika Yulia
Jurnal Ilmiah Teknologi Informasi Asia Vol 18 No 1 (2024): Volume 18 Nomor 1 (8)
Publisher : LP2M Institut Teknologi dan Bisnis ASIA Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32815/jitika.v18i1.991

Abstract

Malaria is a dangerous and potentially deadly disease in Indonesia. The spread and transmission of malaria occurs very rapidly. The aim of this study was to identify clusters within the state based on the intensity of malaria cases. In this study, K-means was applied to the clustering process using the values ​​of K=2, K=3, and K=5. This means that the Davis-Boldan index value for K=2 is 0.033, the Davis-Boldan index value for K=3 is 0.034, and the Davis-Boldan index value for K=5 is 0.262. The research results show that using K-Means with K=2 yields the best cluster with the lowest Davies-Bouldin index value (0.033). This will help the government plan more effective preventive measures in different provinces of Indonesia in the coming years. Therefore, this study makes an important contribution to malaria control efforts to reduce malaria incidence and public health impact in Indonesia.
Co-Authors Suastika Yulia Riska