Penerapan Metode Clustering pada Penyakit Abses Berdasarkan Faktor Penyebab
DOI:
https://doi.org/10.61132/saturnus.v2i4.343Keywords:
K-Means Algorithms, Data Mining, Abscess DiseaseAbstract
An abcess is a collection of pus in an indefinite space in the body, an abscess can appear on the surface of the skin and can appear in the tissues of an organ. Abscesses occur due to an infectious process or from parasitic bacteria due to foreign bodies, such as splinters, bullet wounds, needles. Many patients come with complaints of pain, swelling, redness, fever and others. Therefore, to overcome this problem, it is necessary to take quick action to help reduce and deal with the problem of abscess disease among the community by using the clustering method do that it can help agencies in conducting socialization so that the communinty knows more about the factors that cause abscess disease and how to handle it. From this research courced at tha Binjai estate Health Center which consists of several variables, namely age, type of abscess disease data that often appears, the abscess disease data that often appears after doing the 2 cluster process is with age is 26-35 years, with the type of abscess disease is dental abscess, and the casual factor is not maintaining dental hygiene.
References
Arhami, M.,& Nasir, M. R.indah Utami, E. . 1st ed. (2020). Data Mining. cv andi offset. https://books.google.co.id/books/about/Data_Mining_Algoritma_dan_Implementasi.html?id=AtcCEAAAQBAJ&redir_esc=y
Aryani, A., Fardani, S. R., Hayuti, T. G., Ginari, A. P. A., & Hartomo, B. T. (2022). Penegakan Diagnosis dan Penatalaksanaan Abses Submandibula. Indonesian Journal of Dentistry, 2(1), 7. https://doi.org/10.26714/ijd.v2i1.9866
Boyke Purba, R., Rifka Sarma Agoestina, F. S., Tambunan, H. S., & Nasution, R. A. (2022). Pemanfaatan Algoritma K-Means untuk Pengelompokkan Pasien Penyakit Infeksi Saluran Pernafasan Akut (ISPA). SATESI: Jurnal Sains Teknologi Dan Sistem Informasi, 2(1), 60–69. https://doi.org/10.54259/satesi.v2i1.804
Arhami, M.,& Nasir, M. R.indah Utami, E. . 1st ed. (2020). Data Mining. cv andi offset. https://books.google.co.id/books/about/Data_Mining_Algoritma_dan_Implementasi.html?id=AtcCEAAAQBAJ&redir_esc=y
Aryani, A., Fardani, S. R., Hayuti, T. G., Ginari, A. P. A., & Hartomo, B. T. (2022). Penegakan Diagnosis dan Penatalaksanaan Abses Submandibula. Indonesian Journal of Dentistry, 2(1), 7. https://doi.org/10.26714/ijd.v2i1.9866
Astuti, F. (2013). Data Mining (P. Christian (ed.)). cv andi offset.
Br Batubara, D. Y., Andika, B., & Syahputra, R. (2022). Implementasi Metode Certainty Factor Dalam Mendiagnosa Penyakit Abses Gigi Pada Anak. Jurnal Sistem Informasi Triguna Dharma (JURSI TGD), 1(6), 741. https://doi.org/10.53513/jursi.v1i6.5135
Buaton, R. (2019). DATA MINING TIME SERIES (V. Zarlis, M. Efendi, S., & Yasin (ed.); 1st ed.,). Wade Group.
Buulolo, E. (2020). Data Mining. Deepublish.
Dewi, R. (2023). Aplikasi Matlab Untuk Simulasi Pengolahan Sinyal (A. Prijono (ed.)). Zahir Publishing.
Fajri, M. B., & Purnamasari, S. D. (2022). Klasterisasi Pola Penyebaran Penyakit Pasien Berdasarkan Usia Pasien Menggunakan K-Means Clustering. Journal of Information Technology Ampera, 3(3), 317–334. https://journal-computing.org/index.php/journal-ita/index
Indah, W., Sinaga, S., Buaton, R., & Sembiring, H. (2024). Klasifikasi Data Penduduk Pada Pemilihan Umum Di Kota Binjai Menggunakan Algoritma K-Means ( Studi Kasus : KPU Kota Binjai ). 3(2), 95–102.
Prasetyo, E. (2012). Data Mining : konsep dan aplikasi menggunakan MATLAB. cv andi offset.
Priati, & Fauzi, A. (2017). Data Mining dengan Teknik Clustering Menggunakan Algoritma K-Means pada Data Transaksi Superstore. Seminar Nasional Informatika Dan Aplikasinya (SNIA), September, hal. 15-19. http://community.tableau.com.
Santosa, B. (2007). Data Mining Terapan Dengan MATLAB. Graha Ilmu.
Sembiring, M. A. (2021). Penerapan Metode Algoritma K-Means Clustering Untuk Pemetaan Penyebaran Penyakit Demam Berdarah Dengue (Dbd). Journal of Science and Social Research, 4(3), 336. https://doi.org/10.54314/jssr.v4i3.712
Wahyuni, W. A., & Saepudin, S. (2021). Penerapan Data Mining Clustering Untuk Mengelompokkan Berbagai Jenis Merk Mesin Cuci. Seminar Nasional Sistem Informasi Dan Manajemen Informatika Universitas Nusa Putra, 1(1), 306–313.
Yudhistira, A., & Andika, R. (2023). Pengelompokan Data Nilai Siswa Menggunakan Metode K-Means Clustering. 1(1), 20–28.
n, J. N., Hidayati, L., Mutmainnah, M., Umizah, L. P., Junus, R., Romaidha, I., Saputra, H., Surya, S., Narullita, D., Perrianty, F., Tilawati Sitanggang, F., Lestari, T. R., Lufar, N., & Robert, D. (2023). PENGANTAR IMUNOLOGI (1st ed., Vol. 1). PT Media Pustaka Indo.
Br Batubara, D. Y., Andika, B., & Syahputra, R. (2022). Implementasi Metode Certainty Factor Dalam Mendiagnosa Penyakit Abses Gigi Pada Anak. Jurnal Sistem Informasi Triguna Dharma (JURSI TGD), 1(6), 741. https://doi.org/10.53513/jursi.v1i6.5135
Buaton, R. (2019). DATA MINING TIME SERIES (V. Zarlis, M. Efendi, S., & Yasin (ed.); 1st ed.,). Wade Group.
Buulolo, E. (2020). Data Mining. Deepublish.
Fajri, M. B., & Purnamasari, S. D. (2022). Klasterisasi Pola Penyebaran Penyakit Pasien Berdasarkan Usia Pasien Menggunakan K-Means Clustering. Journal of Information Technology Ampera, 3(3), 317–334. https://journal-computing.org/index.php/journal-ita/index
Sembiring, M. A. (2021). Penerapan Metode Algoritma K-Means Clustering Untuk Pemetaan Penyebaran Penyakit Demam Berdarah Dengue (Dbd). Journal of Science and Social Research, 4(3), 336. https://doi.org/10.54314/jssr.v4i3.712
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