Optimasi Algoritma K-Means Menggunakan Metode Elbow dalam Pengelompokan Penyakit Demam Berdarah Dengue (DBD) di Jawa Barat
Abstract
Dengue hemorrhagic fever (DHF) is an acute febrile infectious disease that usually occurs in tropical and subtropical areas of the world and is caused by a virus transmitted by the Aedes mosquito, namely Aedes aegypti and Aedes albopictus. Dengue fever is one of the endemic diseases that almost occurs throughout the world. Indonesia is the country with the highest dengue fever cases in Southeast Asia. One of the provinces with the most cases of dengue fever is West Java. Every year cases of dengue fever have increased and decreased, so cases cannot be controlled properly. This must be a concern for the West Java Government in handling this Dengue Fever disease. To help the Government of West Java, this research conducted a grouping of dengue fever in West Java in 2016-2021. This research uses the Knowledge Discovery in Database (KDD) method. The algorithm used is k-means clustering with the help of the elbow method to get the optimal number of clusters, which is 2 clusters. Cluster 0 with low category consists of 22 regions, and cluster 2 with high category consists of 5 regions. The result of silhouette coefficient evaluation is 0.689 with standard structure criteria
References
Akbar, H., & Maulana Syaputra, E. (2019). Faktor Risiko Kejadian Demam Berdarah Dengue (DBD) di Kabupaten Indramayu. MPPKI (Media Publikasi Promosi Kesehatan Indonesia): The Indonesian Journal of Health Promotion, 2(3), 159–164. https://doi.org/10.31934/mppki.v2i3.626
Hariyanto, M., & Shita, R. T. (2018). Clustering pada Data Mining untuk Mengetahui Potensi Penyebaran Penyakit DBD Menggunakan Metode Algoritma K-Means dan Metode Perhitungan Jarak Euclidean Distance. Sistem Komputer Dan Teknik Informatika, 1(1), 117–122.
Kiki Fatmawati, A. P. W. (2018). Data Mining : Penerapan Rapidminer Dengan K-Means Cluster Pada Daerah Terjangkit Demam Berdarah Dengue ( Dbd ) Berdasarkan Provinsi. CESS (Journal of Computer Engineering System and Science, 3(2), 173–178.
Sari, T. A., Megawaty, M., & Putra, A. (2019). Pengelompokan Penyebaran Penyakit Ispa Di Wilayah Kota Sekayu Menggunakan Algoritma K-Means Clustering (Studi Kasus: Rsud Sekayu). Bina Darma Conference on Computer Science (BDCCS), 1(1), 174–184.
Sembiring, E. M. (2022). Penerapan K-Means Clustering Untuk Pengelompokan Penyebaran Demam Berdarah Dengue (DBD) Di Kabupaten Deli Serdang. TIN: Terapan Informatika Nusantara, 2(11), 673–677. https://doi.org/10.47065/tin.v2i11.1503
Widyatami, A. I., & Suryawan, D. A. (2021). Pengelompokan Daerah Rawan Demam Berdarah Dengue di Provinsi DKI Jakarta. Indonesian of Health Information Management Journal (INOHIM), 9(1), 73–82. https://doi.org/10.47007/inohim.v9i1.241
Kasus DBD Meningkat, Kemenkes Galakkan Gerakan 1 Rumah 1 Jumantik (G1R1J). (15 Juni 2022). Sehat Negeriku Kemenkes RI. https://sehatnegeriku.kemkes.go.id/baca/umum/20220615/0240172/kasus-dbd-meningkat-kemenkes-galakkan-gerakan-1-rumah-1-jumantik-g1r1j/#:~:text=Kementerian%20Kesehatan%20mencatat%20di%20tahun,akibat%20DBD%20mencapai%20432%20kasus.
Jumlah Kasus Penyakit Demam Berdarah Dengue (DBD) Berdasarkan Kabupaten/Kota di Jawa Barat. Open Data Jabar. Diakses pada 30 Juni 2022.https://opendata.jabarprov.go.id/id/dataset/jumlah-kasus-penyakit-demam-berdarah-dengue-dbd-berdasarkan-kabupatenkota-di-jawa-barat
