Bagian 2: Model Arsitektur Neural Network Dengan Kombinasi K-Medoids dan Backpropagation pada kasus Pandemi Covid-19 di Indonesia
DOI:
https://doi.org/10.30865/mib.v4i4.2505Keywords:
COVID-19 Pandemic, K-Medoids, Backpropagation, Prediction, Architectural Models, Neural NetworkAbstract
The aim of the research is to create a prediction model on the best neural network architecture by combining the k-medoids and backpropagation methods in the case of the COVID-19 pandemic in Indonesia. Data obtained from the Ministry of Health is sampled and processed from covid19.go.id and bnpb.go.id. The case raised was the number of the spread of the COVID-19 pandemic in Indonesia as of July 7, 2020, with 34 records. The variables used in this study are the number of positive cases (x1), the number of cases cured (x2), and the number of deaths (x3) by province. The process of data analysis uses the help of RapidMiner software. The solution provided is to combine the k-medoids and backpropagation methods. Where the k-medoids method is mapping the specified cluster. The cluster labels used are high cluster (C1 = red zone), alert cluster (C2 = yellow zone), low cluster (C3 = green zone). The results of cluster mapping are continued to the backpropagation method to predict the accuracy of the existing cluster results. By using the best architectural model 3-2-1, the accuracy value is 94.17% with learning_rate = 0.696. Cluster mapping results obtained nine provinces are in the high cluster (C1 = red zone), three provinces are in the alert cluster (C2 = yellow zone), and 22 provinces are in the low cluster (C3 = green zone). It is expected that the results of the research can provide information to the government in the form of cluster mapping of regions in Indonesia.
References
D. R. Buana, “Analisis Perilaku Masyarakat Indonesia dalam Menghadapi Pandemi Covid-19 dan Kiat Menjaga Kesejahteraan Jiwa,†SALAM; J. Sos. Budaya Syar-i, vol. 7, no. 3, pp. 217–226, 2020, doi: 10.15408/sjsbs.v7i3.15082.
M. Pradana, S. Syahputra, A. Wardhana, B. R. Kartawinata, and C. Wijayangka, “The Effects of Incriminating COVID-19 News on the Returning Indonesians’ Anxiety,†J. Loss Trauma, vol. 0, no. 0, pp. 1–6, 2020, doi: 10.1080/15325024.2020.1771825.
I. M. A. Wirawan and P. P. Januraga, “Forecasting COVID-19 Transmission and Healthcare Capacity in Bali, Indonesia,†J. Prev. Med. Public Health, vol. 53, no. 3, pp. 158–163, 2020, doi: 10.3961/jpmph.20.152.
Nurkholis, “Dampak Pandemi Novel-Corona Virus Disiase (Covid-19) Terhadap Psikologi Dan Pendidikan Serta Kebijakan Pemerintah,†J. PGSD, vol. 6, no. 1, pp. 39–49, 2020, doi: 10.32534/jps.v6i1.1035.
N. Nuraini, K. Khairudin, and M. Apri, “Modeling Simulation of COVID-19 in Indonesia based on Early Endemic Data,†Commun. Biomath. Sci., vol. 3, no. 1, pp. 1–8, 2020, doi: 10.5614/cbms.2020.3.1.1.
W. Swastika, “Studi Awal Deteksi Covid-19 Menggunakan Citra Ct Berbasis Deep,†J. Teknol. Inf. dan Ilmu Komput., vol. 7, no. 3, pp. 629–634, 2020, doi: 10.25126/jtiik.202073399.
A. Pujianto, K. Kusrini, and A. Sunyoto, “Perancangan Sistem Pendukung Keputusan Untuk Prediksi Penerima Beasiswa Menggunakan Metode Neural Network Backpropagation,†J. Teknol. Inf. dan Ilmu Komput., vol. 5, no. 2, p. 157, 2018, doi: 10.25126/jtiik.201852631.
F. Rahman, I. I. Ridho, M. Muflih, S. Pratama, M. R. Raharjo, and A. P. Windarto, “Application of Data Mining Technique using K-Medoids in the case of Export of Crude Petroleum Materials to the Destination Country Application of Data Mining Technique using K-Medoids in the case of Export of Crude Petroleum Materials to the Destination C,†2020, doi: 10.1088/1757-899X/835/1/012058.
I. Kamila, U. Khairunnisa, and 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.
H. Haviluddin, Z. Arifin, A. H. Kridalaksana, and D. Cahyadi, “Prediksi Kedatangan Turis Asing ke Indonesia Menggunakan Backpropagation Neural Networks,†J. Teknol. dan Sist. Komput., vol. 4, no. 4, p. 485, 2016, doi: 10.14710/jtsiskom.4.4.2016.485-490.
A. P. Windarto, U. Indriani, M. R. Raharjo, and L. S. Dewi, “Bagian 1: Kombinasi Metode Klastering dan Klasifikasi (Kasus Pandemi Covid-19 di Indonesia),†J. Media Inform. Budidarma, vol. 4, no. 3, p. 855, 2020, doi: 10.30865/mib.v4i3.2312.
Downloads
Published
Issue
Section
License
This work is licensed under a Creative Commons Attribution 4.0 International License
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under Creative Commons Attribution 4.0 International License that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (Refer to The Effect of Open Access).
