Penerapan Data Mining untuk Menentukan Penyebab Kematian di Indonesia Menggunakan Metode Clustering K-Means

Lili Rahmawati, Alwis Nazir, Fadhilah Syafria, Elvia Budianita, Lola Oktavia, Ihda Syurfi

Abstract


Death in medical science is studied in a scientific discipline called tanatology. death is not only experienced by elderly people, but also can be experienced by young people, teenagers, or even babies. Death can be caused by various factors, namely, due to illness, old age, accidents, and so on. Based on information provided by the World Health Organization (WHO), there are five highest causes of death including ischemic heart disease, Alzheimer's, stroke, respiratory disorders, neonatal conditions. In this study, k-means is used to group causes of death in Indonesia based on the number of deaths that occur to determine the cases of death that have the most impact on the high mortality rate in Indonesia. Knowing what these death cases are will provide early preparation in anticipating the causes of death in Indonesia. The purpose of this study was to classify mortality rates based on the number of causes of death which were included in the low, medium, and high clusters by applying the K-Means method. In this study the authors used the K-Means clustering algorithm to classify death rates in data on causes of death in Indonesia from 2017-2021. The results of this study formed 3 clusters which were evaluated using the Davies Bouldin Index (DBI) in Rapidminer with a value of 0.259. Clustering results from a total of 21 cases obtained high, medium and low clusters. This cluster grouping was obtained according to the number of deaths per case, namely the first cluster (C0) was low with 17 cases, the second cluster (C1) was moderate with 3 cases and the third cluster (C2) was high with 1 case.

Keywords


Clustering; Data Mining; Mortality; K-Means; Rapidminer

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References


I. Aflanie, N. Nirmalasari, and M. H. Arizal, Ilmu Kedokteran Forensik dan Medikolegal. 2017.

Ninla Elmawati Falabiba, “Modul Forensik Tanatologi,†Univ. Andalas Padang, no. perubahan pada mayat paska mati, pp. 1–12, 2019.

Erza, “Fakultas Kedokteran Universitas Andalas,†J. Fak. Kedokt. Univ. Andalas 1, vol. 2007, pp. 6–9, 2019, [Online]. Available: http://scholar.unand.ac.id/61716/2/2. BAB 1 (Pendahuluan).pdf.

A. G. Parinduri, “Buku ajar kedokteran forensik & medikolegal pedoman bagi mahasiswa kedokteran,†pp. 27–32, 2020, [Online]. Available: http://umsupress.umsu.ac.id/.

R. F. Ramadhan and W. S. Ardias, “Konstrual diri (,†no. April, pp. 79–90, 2019.

A. P. Anggraini, “5 Penyebab Tertinggi Kematian Menurut Data WHO,†12 Agustus, 2021. https://health.kompas.com/read/2021/08/12/120700868/5-penyebab-tertinggi-kematian-menurut-data-who?page=all.

N. Zakiah, “7 Penyakit Penyebab Kematian Tertinggi di Indonesia,†15 Maret, 2020. https://www.idntimes.com/health/medical/nena-zakiah-1/penyakit-penyebab-kematian-tertinggi-di-indonesia.

Badan Pusat Statistik, “Jumlah Korban Meninggal, Hilang, dan Terluka Terkena Dampak Bencana Per 100.000 Orang.†https://www.bps.go.id/indikator/indikator/view_data/0000/data/1246/sdgs_13/1.

P. M. C. Abrianto, “Penerapan Metode K-Means Clustering Untuk Pengelompokkan Pasien Penyakit Liver,†JATI (Jurnal Mhs. Tek. Inform., vol. 2, no. 2, pp. 247–255, 2018.

N. Vitalaya and R. T. Prasetio, “Implementasi Algoritma K-Means Clustering Untuk Pengelompokan Penyebaran Pneumonia Pada Balita Di Kota Bandung,†POTENSI (eProsiding Sist. Informasi), vol. 1, no. 1, pp. 108–116, 2020, [Online]. Available: http://eprosiding.ars.ac.id/index.php/psi%0Ahttp://eprosiding.ars.ac.id/index.php/psi/article/view/291.

R. Kurniawan, & S., and R. Dewi, “Penerapan Algoritma K-Means Clustering Dalam Persentase Merokok Pada Penduduk Umur Di Atas 15 Tahun Menurut Provinsi,†J. Sist. Komput. dan Inform., vol. 2, no. 2, pp. 178–186, 2021, doi: 10.30865/json.v2i2.2770.

S. A. Y. Nasution, P. Poningsih, and ..., “Penerapan Algoritma K-Means Pada Penjualan Frozen Food Pada UD Soise Sosis Pematangsiantar,†J. Sist. …, vol. 2, pp. 171–177, 2021, doi: 10.30865/json.v2i2.2768.

N. W. S. Utami Ni Nyoman, “Penerapan Data Mining Untuk Klasifikasi Penyebab Kematian Menggunakan Algoritma Support Vector Machine,†J. Ilm. Ilmu Terap. Univ. Jambi|JIITUJ|, vol. 4, no. Vol. 4 No. 2 (2020): Volume 4, Nomor 2, Desember 2020, pp. 234–240, 2020, [Online]. Available: https://online-journal.unja.ac.id/JIITUJ/article/view/13268/11199.

D. Abdullah and D. Saputra, “Aplikasi Penjadwalan Pengadaan Barang Menggunakan Algoritma Apriori,†no. January, 2016.

R. Yani, A. Nazir, M. Affandes, R. Mai Candra, and A. Akhyar, “Implementasi Data Mining Untuk Menemukan Pola Asosiasi Data Tracer Study Menggunakan Algoritma Apriori,†J. Nas. Komputasi dan Teknol. Inf., vol. 5, no. 3, pp. 383–390, 2022, [Online]. Available: https://ojs.serambimekkah.ac.id/jnkti/article/view/4412.

A. Nur Khormarudin, “Teknik Data Mining: Algoritma K-Means Clustering,†J. Ilmu Komput., pp. 1–12, 2016, [Online]. Available: https://ilmukomputer.org/category/datamining/.

D. Merawati and Rino, “Penerapan data mining penentu minat Dan bakat siswa Smk dengan metode C4 . 5,†J. Algor, vol. 1, no. 1, pp. 28–37, 2019.

F. Indriyani and E. Irfiani, “Clustering Data Penjualan pada Toko Perlengkapan Outdoor Menggunakan Metode K-Means,†JUITA J. Inform., vol. 7, no. 2, p. 109, 2019, doi: 10.30595/juita.v7i2.5529.

D. Darmansah, “Analisa Penyebab Kerusakan Tanaman Cabai Menggunakan Metode K-Means,†JATISI (Jurnal Tek. Inform. dan Sist. Informasi), vol. 7, no. 2, pp. 126–134, 2020, doi: 10.35957/jatisi.v7i2.309.

S. Defiyanti, M. Jajuli, and N. Rohmawati, “Optimalisasi K-MEDOID dalam Pengklasteran Mahasiswa Pelamar Beasiswa dengan CUBIC CLUSTERING CRITERION,†J. Nas. Teknol. dan Sist. Inf., vol. 3, no. 1, pp. 211–218, 2017, doi: 10.25077/teknosi.v3i1.2017.211-218.

A. A. Lesmana et al., “Implementasi Algoritma K-Means Untuk Clustering Penyakit Hiv / Aids Di Indonesia Implementation of K-Means Algorithm for Clustering of Hiv / Aids Disease in Indonesia,†vol. 6, no. 2, pp. 5564–5580, 2019.

R. Helilintar, I. N. Farida, and R. H. Irawan, “Penerapan Metode K-Means Clustering Pada Data Penerimaan Mahasiswa Baru,†Semin. Nas. Teknol. Inf. dan KomunikasiSENATIK|2018|Literasi Digit. pada Era Revolusi Ind. 4.0, pp. 14–20, 2018.

R. NOVIANTO, “Penerapan Data Mining menggunakan Algoritma K-Means Clustering untuk Menganalisa Bisnis Perusahaan Asuransi,†JATISI (Jurnal Tek. Inform. dan Sist. Informasi), vol. 6, no. 1, pp. 85–95, 2019, doi: 10.35957/jatisi.v6i1.150.




DOI: https://doi.org/10.30865/json.v4i3.5912

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