Implementasi Data Mining Dalam Pengelompokan Data Penyakit Pasien Menggunakan Metode K-Means Clustering
Keywords:
K-Means Clustering,, patient data, healthcareAbstract
This study aims to identify the pattern and distribution of diseases at the Mambi Health Center using the K-Means Clustering method. Patient data includes age, gender, address, and type of disease suffered. This method was chosen because of its ability to group data based on similar characteristics, making it easier to identify dominant diseases. The results reveal the age groups susceptible to certain diseases, the geographical distribution of diseases with high prevalence, and the types of diseases often encountered at the Puskesmas. These insights are expected to help Puskesmas in allocating resources effectively, designing more appropriate prevention programs, and improving the quality of health services. This study also provides recommendations for disease management strategies based on the identified groups, so as to support efforts to improve public health.
References
. Laode muhammad alghazali,s.kep.,ns. 2023. Puskesmas mambi.
. Damanik, y.f.s.y. Et al. (2021) ‘penerapan data mining untuk pengelompokan penyebaran covid-19 di sumatera utara menggunakan algoritma k- means’, jurnal ilmu komputer dan informatika,1(2),pp.109–132.availableat: https://doi.org/10.54082/jiki.13.
. Ali, a. (2019) ‘klasterisasi data rekam medis pasien menggunakan metode k- means clustering di rumah sakit anwar medika balong bendo sidoarjo’, matrik?: jurnal manajemen, teknik informatika dan rekayasa komputer, 19(1), pp. 186–195. Available at: https://doi.org/10.30812/matrik.v19i1.529.
. Harjanto, t.d., vatresia, a. And faurina, r. (2021) analisis penetapan skala prioritas penanganan balita stunting menggunakan metode dbscan clustering, jurnal rekursif. Available at: http://ejournal.unib.ac.id/index.php/rekursif/30.
. Deni, r. And setiawan, p. (2018) penerapan metode k-means clustering untuk analisis potensi produksi komoditi buah pada kabupaten lumajang, jurnal mahasiswa teknik informatika.
. Maulia, s., serasi ginting, b. And sihombing, a. (2021) ‘implementasi data mining pengelompokan jenis penyakit pasien menggunakan metode clustering (studi kasus?: puskesmas sambirejo)’, jik), 5(1).
. May, p. And abrianto, c. (2018) penerapan metode k-means clustering untuk pengelompokkan pasien penyakit liver, jurnal mahasiswa teknik informatika . Available at: http://archive. Ics.uci.edu/ml/.
. Ordila, r. Et al. (2020). ‘penerapan data mining untuk pengelompokan data rekam medis pasien berdasarkan jenis pensyakit dengan algoritma
. Rahmawati, l., widya sihwi, s. And suryani, e. (2016) ‘analisa clustering menggunakan metode k-means dan hierarchical clustering (studi kasus?: dokumen skripsi jurusan kimia, fmipa, universitas sebelas maret)’, jurnal teknologi & informasi itsmart, 3(2), p. 66. Available at: https://doi.org/10.20961/its.v3i2.654.
. Adani, n.f. Et al. (no date) ‘implementasi data mining untuk pengelompokan data penjualan berdasarkan pola pembelian menggunakan algoritma k- means clustering pada toko syihan stmik triguna dharma ** program
. Clustering (studi kasus?: poli klinik pt.inecda)’, jurnal ilmu komputer, 9(2),pp.148–153.availableat: https://doi.org/10.33060/jik/2020/vol9.iss2.181.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2024 Seminar Nasional Sistem Informasi dan Teknologi (SISFOTEK)
This work is licensed under a Creative Commons Attribution 4.0 International License.
http://creativecommons.org/licenses/by/4.0
