Pengelompokkan Daerah Rawan Demam Berdarah (DBD) di Jawa Timur Menggunakan Metode K-Means
Keywords:
Dengue Hemorrhagic Fever, Classification, K-MeansAbstract
Tropical diseases are common in areas with tropical and subtropical climates. As a country with a tropical climate, Indonesia is vulnerable to various tropical diseases. A large number of tropical diseases can occur in the temperate climate zone, differing only in the frequency with which they are affected. Dengue hemorrhagic fever is a tropical disease in Indonesia. DHF occurs as a result of infection with the dengue virus which is transmitted through the bite of the female Aedes aegypti mosquito. The high prevalence of DHF in East Java requires a data collection process to identify areas that are frequently infected with DHF. Therefore, we need a clustering system that can help classify areas that often experience DHF cases. This study aims to find out which districts/cities have the predominant cases of dengue fever. The clustering method used is K-Means clustering. Based on the research conducted, 2 clusters were obtained with a silhouette coefficient value of 0.76. Cluster 1 covers 36 districts/cities and is an area with a low level of vulnerability to dengue fever, while cluster 2 covers 2 districts/cities and is an area with a high level of vulnerability to dengue fever.
References
Masluhiya, S., AF, Wibowo, R. C. A., & Luthfin, A. Eksplorasi Sebaran Penyakit Demam Berdarah Dengue (DBD) dan Pneumonia di Kota Malang. JUMANTIK (Jurnal Ilm. Penelit. Kesehatan), 7(2), 134, 2022, doi: 10.30829/jumantik.v7i2.10402.
Sembiring, M. A. Penerapan Metode Algoritma K-Means Clustering Untuk Pemetaan Penyebaran Penyakit Demam Berdarah Dengue (Dbd). J. Sci. Soc. Res., 4(3), p. 336, 2021, doi: 10.54314/jssr.v4i3.712.
Kurniawan, R. E., Makrifatullah, N. A., Rosar, N., Triana, Y., & Kunci, K. Hubungan Sanitasi Lingkungan Rumah Tinggal dengan Kejadian Demam Berdarah. J. Ilm. Multi Disiplin Indones., 2(1), pp. 163–173, 2022, [Online]. Available: https://katadata.co.id/berita/2020/01/06/baru-83-peserta-bpjs-kesehatan-per-akhir-2019-
Widiastuti, S. H., & Jumardi, R. Pengelompokan Daerah Rawan Demam Berdarah dengan Metode K-Means Clustering. J. Inf. dan Teknol., 4(4), pp. 185–190, 2022, doi: 10.37034/jidt.v4i4.213.
Amelia, D., Padilah, T. N., & Jamaludin, A. Optimasi Algoritma K-Means Menggunakan Metode Elbow dalam Pengelompokan Penyakit Demam Berdarah Dengue (DBD) di Jawa Barat. J. Ilm. Wahana Pendidik., 8(11), pp. 207–215, 2022, [Online]. Available: http://jurnal.peneliti.net/index.php/JIWP/article/view/1907
Azwan, M., et al. Penerapan Algoritma K-Means Clustering dan Correlation Matrix Untuk Menganalisis Risiko Penyebaran Demam Berdarah di Kota Pekanbaru. JIMP J. Inform. Merdeka Pasuruan, 6(3), pp. 1–6, 2022.
Yuniar, V. T., Joegijantoro, R., & Cahyani, S. D. Pengaruh Tingkat Kepadatan Jentik Aedes Aegypti Terhadap Kejadian Demam Berdarah Dengue (DBD) di Desa Pandansari Kecamatan. J. Hig. Sanitasi, 2(2), pp. 57–63, 2022.
Dinata, R. K., Safwandi, S., Hasdyna, N., & Azizah, N. Analisis K-Means Clustering pada Data Sepeda Motor. INFORMAL Informatics J., 5(1), p. 10, 2020, doi: 10.19184/isj.v5i1.17071.
Herlinda, V., & Darwis, D. Analisis Clustering Untuk Recredesialing Fasilitas Kesehatan Menggunakan Metode Fuzzy C-Means. Darwis, Dartono, 2(2), pp. 94–99, 2021, [Online]. Available: http://jim.teknokrat.ac.id/index.php/JTSI
Nabila, Z., Rahman Isnain, A., & Abidin, Z. Analisis Data Mining Untuk Clustering Kasus Covid-19 Di Provinsi Lampung Dengan Algoritma K-Means. J. Teknol. dan Sist. Inf., 2(2), p. 100, 2021, [Online]. Available: http://jim.teknokrat.ac.id/index.php/JTSI
Gunawan, H., & Purwayoga, V. Data Mining Menggunakan Algoritma K-Means Clustering Untuk Mengetahui Potensi Penyebaran Virus Corona Di Kota Cirebon. J. Sisfokom (Sistem Inf. dan Komputer), 11(1), pp. 1–8, 2022, doi: 10.32736/sisfokom.v11i1.1316.
Wahyu Pribadi, W., Yunus, A., & Wiguna, A. S. Perbandingan Metode K-Means Euclidean Distance Dan Manhattan Distance Pada Penentuan Zonasi Covid-19 Di Kabupaten Malang. JATI (Jurnal Mhs. Tek. Inform., 6(2), pp. 493–500, 2022, doi: 10.36040/jati.v6i2.4808.
Siregar, P. P., Solikhun, S., & Siregar, Z. A. Penerapan Metode K-Means Dalam Mengelompokkan Persebaran Lahan Kritis Di Indonesia Berdasarkan Provinsi. Resolusi Rekayasa Tek. Inform. dan Inf., 2(4), pp. 145–151, 2022, doi: 10.30865/resolusi.v2i4.335.
Paembonan, S., & Abduh, H. Penerapan Metode Silhouette Coefficient untuk Evaluasi Clustering Obat. PENA Tek. J. Ilm. Ilmu-Ilmu Tek., 6(2), p. 48, 2021, doi: 10.51557/pt_jiit.v6i2.659.
Farissa, R. A., Mayasari, R., & Umaidah, Y. Perbandingan Algoritma K-Means dan K-Medoids Untuk Pengelompokkan Data Obat dengan Silhouette Coefficient di Puskesmas Karangsambung. J. Appl. Informatics Comput., 5(2), pp. 109–116, 2021, doi: 10.30871/jaic.v5i1.3237.
Agustian, D. R., & Darmawan, B. A. Analisis Clustering Demam Berdarah Dengue Dengan Algoritma K-Medoids (Studi Kasus Kabupaten Karawang). JIKO (Jurnal Inform. dan Komputer), 6(1), p. 18, 2022, doi: 10.26798/jiko.v6i1.504.
Anggraeni, D. S., & Enri, U. Pengelompokkan Data Kemiskinan Provinsi Jawa Barat Menggunakan Algoritma K-Means dengan Silhouette Coefficient. Temat. J. Teknol. Inf. Komun., 9(1), pp. 29–35, 2022, [Online]. Available: http://jurnal.plb.ac.id/index.php/tematik/article/view/901.
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