Aplikasi Data Mining untuk Clustering Daerah Penyebaran Penyakit Diare di DKI Jakarta Menggunakan Algoritma K-MEANS

Teguh Budi Santos

Abstract


Diarrhea is a disease that makes sufferers defecate more than 4 times, diarrhea usually strikes all people, including toddlers, teens and adults. The increasing population density in DKI Jakarta Province in 2017 around 10,177,924 inhabitants spread over 6 cities consisting of 44 districts and 267 villages. To be able to see the area of diarrhea distribution, it is necessary to make a grouping based on the attributes used consisting of JSP, JSSP, SHARING and OD in order to obtain the center of the diarrhea spread point. K-Means algorithm is very suitable in clustering the spread of diarrhea Kelurahan. To determine the centroid starting point based on diarrhea sufferers as a parameter in determining C1, C2 and C3 which get C1 is Duren Tiga Village, C2 is Kebon Baru Village and C3 is Bendungan Hilir Village. The results of grouping based on the attributes used get C1 totaling 11 Kelurahans, C2 totaling 34 Kelurahans and C3 totaling 43 Kelurahans from 88 Kelurahan data used in which C1 is categorized as a diarrhea prone point, C2 is categorized as a possible spread of diarrhea and C3 is categorized as a Kelurahan that is safe from spread of diarrhea.


Keywords


Diarrheal Disease; K-Means Application

Full Text:

PDF

References


Atthina, N., & Iswari, L. (2014, Juni). Klasterisasi Data Kesehatan Penduduk Untuk Menentukan Rentang Derajat Kesehatan Dengan Metode K-Means. Seminar Nasional Aplikasi Teknologi Informasi (SNATI).

BPS PROVINSI DKI JAKARTA. (2017, Januari 30). jakarta.bps.go.id. Retrieved from BPS Provinsi DKI Jakarta: https://jakarta.bps.go.id/statictable/2017/01/30/142/jumlah-penduduk-menurut-kelompok-umur-dan-jenis-kelamin-di-provinsi-dki-jakarta-2015.html

Fauzi, M., & Yudi. (2017, Juli). Penerapan Algoritma K-Means Clustering Untuk Mendeteksi Penyebaran Penyakit TBC. Teknik Informatika KAPUTAMA, 1(2), 1-7.

KEMKES RI. (2016). Data dan Informasi. Jakarta: Kementerian Kesehatan Republik Indonesia.

KEMKES RI. (2017). Data dan Informasi. Jakarta: Kementerian Kesehatan Republik Indonesia.

Larose, D.T. (2005). Discovering Knowledge in Data

Munawar. (2005). Pemodelan Visual dengan UML . Yogyakarta: Graha Ilmu.

Munggarah, T. P., & T. H. (2015, Maret). Penerapan Algoritma C.45 Untuk Diagnosa Penyakit Diare Pada Anak Balita Berbasis Mobile. Swabumi, vol : II No.1.

Nasari, F., & Sinaturi, C. J. (2016, Desember). Penerapan Algoritma K-Means Clustering Untuk Pengelompokkan Penyebaran Diare di Kabupaten. Cogito Smart Jurnal, Vol 2, No 2, 108, 108.

Santoso, T. B. (2014). Analisa dan Penerapan Metode C4.5 untuk Prediksi Loyalitas Pelanggan. Jurnal Ilmiah Fakultas Teknik - LIMIT'S Vol.10 (1) Hal.22-31.

Tan P, Steinbach M, Kumar V. (2006). Introduction to Data Mining. In E. Prasetyo, Data Mining - Konsep dan Aplikasi Menggunakan MATLAP (p. 2). Gresik: ANDI Yogyakarta

UNICEF. (2009). Diarrhoea:Why children are still dying and what can be done. United State: The United Nations Children’s Fund (UNICEF)/ World Health Organization (WHO).

Widoyono. (2008). Penyakit Tropis Epidemiologi, Penularan, Pencegahan dan Pemberantasanya. Jakarta: Erlanga




DOI: http://dx.doi.org/10.22441/fifo.2019.v11i2.003

Refbacks



Jurnal Ilmiah FIFO
Portal ISSNPrint ISSN: 2085-4315
Online ISSN: 2502-8332

Sekretariat
Fakultas Ilmu Komputer
Universitas Mercu Buana
Jl. Raya Meruya Selatan, Kembangan, Jakarta 11650
Tlp./Fax: +62215871335

http://publikasi.mercubuana.ac.id/index.php/fifo

e-mail:[email protected]

Creative Commons Licence
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

Web
Analytics Made Easy - StatCounter
View My Stats

 

width= width=