Penerapan Algoritma K-Means dan K-Medoid untuk Pengelompokkan Data Pasien Covid-19
-
Umairah Rizkya Gurning
*
Universitas Islam Negeri Sultan Syarif Kasim Riau, Pekanbaru,
Indonesia
- Mustakim Mustakim Universitas Islam Negeri Sultan Syarif Kasim Riau, Pekanbaru, Indonesia (*) Corresponding Author
Abstract
At the end of 2019 in Wuhan, China, a new virus was discovered, that is Corona Virus Disease 2019. This virus causes serious health problems and has been declared as pandemic since March 11, 2020. It has caused death and claimed thousands of lives. This virus spreads very quickly and in various ways such as direct contact with patients, travelers, owners of congenital diseases and many other transmissions. To suppress the spread of this virus, the government has carried out various ways such as social distancing and screening or impromptu swabs in crowded centers. Due to the many types of transmission from this virus, this research was conducted to classify Covid-19 cases in Dumai City. It is hoped that the results of this study can be used as an illustration of the grouping of Covid-19 patient data by applying K-Means and K-Medoid as a grouping algorithm based on the type of transmission, age, gender, health services and district. Based on this research, the K-Means algorithm is more optimal than K-Medoid in classifying Covid-19 patient data, especially in Dumai City. It is proven that the best DBI K-Means value is 0.139 with k = 4
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References
D. Y. Liliana, H. Maulana, and A. Setiawan, “Data Mining untuk Prediksi Status Pasien Covid-19 dengan Pengklasifikasi Naïve Bayes,” J. Multinetics, vol. 7, no. 1, pp. 48–53, 2021.
F. Adiba, “Penerapan Data Mining dalam Mengklasifikasikan Tingkat Kasus Covid-19 di Sulawesi Selatan Menggunakan Algoritma Naive Bayes,” Indones. J. Fundam. Scienes, vol. 7, no. 1, pp. 18–28, 2021.
G. Moguolo and L. Nanni, “A Critic Evaluation of Methods for COVID-19 Automatic Detection from X-Ray Images,” http://arxix.org/abs/2004.12823, 2020.
N. Nurhalimah, “Upaya Bela Negara Melalui Sosial Distancing Dan Lockdwon,” Sekol. Tinggi Tarb. Insa. Kamil, pp. 1–6, 2020.
Noviyanto, “Penerapan Data Mining dalam Mengelompokkan Jumlah Kematian,” J. Inform. dan Komput., vol. 22, no. 2, pp. 183–188, 2020.
G. D. Rembulan, T. Wijaya, D. Palullungan, K. N. Alfina, and M. Qurthuby, “Kebijakan Pemerintah Mengenai Coronavirus Disease (COVID-19) di Setiap Provinsi di Indonesia Berdasarkan Analisis Klaster,” JIEMS (Journal Ind. Eng. Manag. Syst., vol. 13, no. 2, 2020, doi: 10.30813/jiems.v13i2.2280.
D. D. Darmansah and N. W. Wardani, “Analisis Pesebaran Penularan Virus Corona di Provinsi Jawa Tengah Menggunakan Metode K-Means Clustering,” JATISI (Jurnal Tek. Inform. dan Sist. Informasi), vol. 8, no. 1, pp. 105–117, 2021, doi: 10.35957/jatisi.v8i1.590.
Z. Zaharah, G. I. Kirilova, and A. Windarti, “Impact of corona virus outbreak towards teaching and learning activities in Indonesia,” SALAM J. Sos. dan Budaya Syar-i, vol. 7, no. 3, pp. 269–282, 2020.
M. Sukmana, M. Aminuddin, and D. Nopriyanto, “Indonesian government response in COVID-19 disaster prevention,” East African Sch. J. Med. Sci., vol. 3, no. 3, pp. 81–86, 2020.
Covid-19.go.id, “Situasi Covid-19 Di Indonesia,” http://covid19.go.id, 2021. .
Riau Tanggap Virus Corona, “Sebaran Covid-19 Provinsi Riau,” https://corona.riau.go.id, 2021.
C. Long et al., “Diagnosis of the Coronavirus disease (COVID-19): rRT-PCR or CT?,” Eur. J. Radiol., vol. 126, p. 108961, 2020.
N. Mona, “Konsep isolasi dalam jaringan sosial untuk meminimalisasi efek contagious (kasus penyebaran virus corona di Indonesia),” J. Sos. Hum. Terap., vol. 2, no. 2, 2020.
A. Hafeez, S. Ahmad, S. A. Siddqui, M. Ahmad, and S. Mishra, “A review of COVID-19 (Coronavirus Disease-2019) diagnosis, treatments and prevention,” EJMO, vol. 4, no. 2, pp. 116–125, 2020.
S. Sindi, W. R. O. Ningse, I. A. Sihombing, F. Ilmi R.H.Zer, and D. Hartama, “Analisis algoritma K-Medoids clustering dalam pengelompokan penyebaran Covid-19 di Indonesia,” Jti (Jurnal Teknol. Informasi), vol. 4, no. 1, pp. 166–173, 2020.
C. A. Sugianto, A. H. Rahayu, and A. Gusman, “Algoritma K-Means Untuk Pengelompokkan Penyakit Pasien Pada Puskesmas Cigugur Tengah,” J. Inf. Technol., vol. 2, no. 2, pp. 39–44, 2020.
A. F. Watratan and D. Moeis, “Implementasi Algoritma Naive Bayes Untuk Memprediksi Tingkat Penyebaran Covid-19 Di Indonesia,” J. Appl. Comput. Sci. Technol., vol. 1, no. 1, pp. 7–14, 2020.
Y. Cheng, K. Chen, H. Sun, Y. Zhang, and F. Tao, “Data and knowledge mining with big data towards smart production,” J. Ind. Inf. Integr., vol. 9, no. September, pp. 1–13, 2018, doi: 10.1016/j.jii.2017.08.001.
M. Arhami, M. Kom, and S. T. Muhammad Nasir, Data Mining-Algoritma dan Implementasi. Penerbit Andi, 2020.
D. K. Sharma, S. K. Dhurandher, D. Agarwal, and K. Arora, “kROp: k-Means clustering based routing protocol for opportunistic networks,” J. Ambient Intell. Humaniz. Comput., vol. 10, no. 4, pp. 1289–1306, 2019.
S. A. Abbas, A. Aslam, A. U. Rehman, W. A. Abbasi, S. Arif, and S. Z. H. Kazmi, “K-Means and K-Medoids: Cluster Analysis on Birth Data Collected in City Muzaffarabad, Kashmir,” IEEE Access, vol. 8, pp. 151847–151855, 2020.
I. Kamila, U. Khairunnisa, and M. Mustakim, “Perbandingan Algoritma K-Means dan K-Medoids untuk Pengelompokan Data Transaksi Bongkar Muat di Provinsi Riau,” J. Ilm. Rekayasa dan Manaj. Sist. Inf., vol. 5, no. 1, pp. 119–125, 2019.
S. Nawrin, M. R. Rahman, and S. Akhter, “Exploreing k-means with internal validity indexes for data clustering in traffic management system,” Int. J. Adv. Comput. Sci. Appl., vol. 8, no. 3, pp. 264–272, 2017.
P. Prasetyawan, I. Ahmad, R. I. Borman, Y. A. Pahlevi, and D. E. Kurniawan, “Classification of the Period Undergraduate Study Using Back-propagation Neural Network,” in 2018 International Conference on Applied Engineering (ICAE), 2018, pp. 1–5.
S. Pramono, I. Ahmad, and R. I. Borman, “ANALISIS POTENSI DAN STRATEGI PENEMBAAN EKOWISATA DAERAH PENYANGA TAMAN NASIONAL WAY KAMBAS,” J. Teknol. dan Sist. Inf., vol. 1, no. 1, pp. 57–67, 2020.
H. Sulistiani, I. Darwanto, and I. Ahmad, “Penerapan Metode Case Based Reasoning dan K-Nearest Neighbor untuk Diagnosa Penyakit dan Hama pada Tanaman Karet,” JEPIN (Jurnal Edukasi dan Penelit. Inform., vol. 6, no. 1, pp. 23–28, 2020.
R. Adha, N. Nurhaliza, U. Sholeha, and M. Mustakim, “Perbandingan Algoritma DBSCAN dan K-Means Clustering untuk Pengelompokan Kasus Covid-19 di Dunia,” SITEKIN J. Sains, Teknol. dan Ind., vol. 18, no. 2, pp. 206–211, 2021.
H. Lu, C. W. Stratton, and Y. Tang, “Outbreak of pneumonia of unknown etiology in Wuhan, China: The mystery and the miracle,” J. Med. Virol., vol. 92, no. 4, p. 401, 2020.
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