Malaria Disease Clustering Analysis Using the K-Means Method in Indonesia

  • Suastika Yulia Riska Institut Teknologi dan Bisnis Asia

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.

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References

[1] A. L. Kalua, Veronika H, and D. T. Salaki, “Sistem Pakar Diagnosa Penyakit Malaria dengan Certainty Factor dan Forward Chaining,” J. Inf. Technol. Softw. Eng. Comput. Sci., vol. 1, no. 1, pp. 22–34, 2022, doi: 10.58602/itsecs.v1i1.10.
[2] Y. Yohannes, S. Devella, and K. Arianto, “Deteksi Penyakit Malaria Menggunakan Convolutional Neural Network Berbasis Saliency,” JUITA J. Inform., vol. 8, no. 1, p. 37, 2020, doi: 10.30595/juita.v8i1.6671.
[3] Karmila, H. S. Tambunan, Sumarno, and A. P. Windarto, “Penerapan Data Mining K-Means dalam Mengelompokkan Kasus Penyakit Malaria Berdasarkan Provinsi dengan Aplikasi RapidMiner,” Reg. Dev. Ind. Heal. Sci. Technol. Art Life, pp. 31–40, 2017, [Online]. Available: https://ptki.ac.id/jurnal/index.php/readystar/article/view/4/pdf (05 Juni 2020).
[4] E. Sari and R. A. Syakurah, “Analisis Manajemen Pelatihan Kader Malaria Pada Populasi Suku Anak Dalam Di Kabupaten Musi Rawas Utara,” J.Abdimas Community Heal., vol. 4, no. 1, pp. 01–08, 2023, doi: 10.30590/jach.v4n1.582.
[5] S. Sindi, W. R. O. Ningse, I. A. Sihombing, F. I. R.H.Zer, and D. Hartama, “Analisis Algoritma K-Medoids Clustering Dalam Pengelompokan Penyebaran Covid-19 Di Indonesia,” J. Teknol. Inf., vol. 4, no. 1, pp. 166–173, 2020, doi: 10.36294/jurti.v4i1.1296.
[6] Y. Bete, D. Santos, R. Lani, A. Ewal, and B. J. Lenggu, “Menentukan Titik Rawan Malaria Di Provinsi Nusa Tenggara Timur Menggunakan Metode K-Means Clustering,” vol. 1, no. 4, 2023.
[7] A. M. Sroyer, S. A. Mandowen, and F. Reba, “Analisis Cluster Penyakit Malaria Provinsi Papua Menggunakan Metode Single Linkage Dan K-Means,” J. Nas. Teknol. dan Sist. Inf., vol. 7, no. 3, pp. 147–154, 2022, doi: 10.25077/teknosi.v7i3.2021.147-154.
[8] A. F. Zohra, S. Anwar, A. Fitri, and M. H. Nasution, “Klasifikasi Wilayah Provinsi Aceh Berdasarkan Tingkat Kerentanan Kasus Malaria Tahun 2015 – 2018,” J. Kesehat. Lingkung. Indones., vol. 18, no. 1, p. 25, 2019, doi: 10.14710/jkli.18.1.25-33.
[9] Y. Nurohmah, R. Mayasari, and B. Nurina Sari, “Optimalisasi Performa K-Means Clustering Dengan Pca Dalam Analisis Tingkat Kemiskinan Di Jawa Barat,” JATI (Jurnal Mhs. Tek. Inform., vol. 7, no. 3, pp. 1657–1665, 2023, doi: 10.36040/jati.v7i3.6884.
[10] R. Ranjawali, A. C. Talakua, and R. T. Abineno, “Clustering Stunting Pada Balita Dengan Metode K- Means Di Puskesmas Kanatang,” SATI Sustain. Agric. Technol. Innov., pp. 80–92, 2023, [Online]. Available: https://ojs.unkriswina.ac.id/index.php/semnas-FST/article/view/587/324.
[11] E. Febrianty, L. Awalina, and W. I. Rahayu, “Optimalisasi Strategi Pemasaran dengan Segmentasi Pelanggan Menggunakan Penerapan K-Means Clustering pada Transaksi Online Retail Optimizing Marketing Strategies with Customer Segmentation Using K-Means Clustering on Online Retail Transactions,” J. Teknol. dan Inf., vol. 13, no. September, pp. 122–137, 2023, doi: 10.34010/jati.v13i2.
Published
2024-03-17
How to Cite
RISKA, Suastika Yulia. Malaria Disease Clustering Analysis Using the K-Means Method in Indonesia. Jurnal Ilmiah Teknologi Informasi Asia, [S.l.], v. 18, n. 1, p. 60-70, mar. 2024. ISSN 2580-8397. Available at: <https://jurnal.stmikasia.ac.id/index.php/jitika/article/view/991>. Date accessed: 01 may 2024. doi: https://doi.org/10.32815/jitika.v18i1.991.