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All Journal Ethos Sistemasi: Jurnal Sistem Informasi Journal of Information Technology and Computer Science (JOINTECS) Jurnal CoreIT DoubleClick : Journal of Computer and Information Technology JUKI : Jurnal Komputer dan Informatika Jurnal Teknik Informatika (JUTIF) ABSYARA: Jurnal Pengabdian Pada Masyarakat International Journal Education and Computer Studies Dedikasi: Jurnal Pengabdian Kepada Masyarakat Room of Civil Society Development
Muhammad Furqan Rasyid
Universitas Dipa Makassar
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Languange, Linguistic, Communication & Media Library & Information Science Mathematics Social Sciences Other

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Journal : Jurnal CoreIT

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Python Model Predicts Covid-19 Cases since Omicron in Indonesia Muhammad Furqan Rasyid
Jurnal CoreIT: Jurnal Hasil Penelitian Ilmu Komputer dan Teknologi Informasi Vol 9, No 1 (2023): June 2023
Publisher : Fakultas Sains dan Teknologi, Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (322.8 KB) | DOI: 10.24014/coreit.v9i1.18908

Abstract

The proposed work uses Support Vector Regression model to predict the new cases, recovered cases, and deaths cases of covid-19 every day during sub-variant omicron spread in Indonesia. We collected data from June 14, 2022, to August 12, 2022 (60 Days). This model was developed in Python 3.6.6 to get the predictive value of the issues mentioned above up to September 21, 2022. The proposed methodology uses a SVR model with the Radial Basis Function as the kernel and a 10% confidence interval for curve fitting. The data collected has been divided into 2 with a size of 40% test data and 60% training data. Mean Squared Error, Root Mean Squared Error, Regression score, and percentage accuracy calculated the model performance parameters. This model has an accuracy above 87% in predicting new cases and recovered patients and 68% in predicting daily death cases. The results show a Gaussian decrease in the number of cases, and it could take another 4 to 6 weeks for it to drop to the minimum level as the origin of the undiscovered omicron sub-variant. RBF (Radial Basis Function) very efficient and has higher accuracy than linear or polynomial regression as kernel of SVR.
Co-Authors Anak Agung Gede Sugianthara Andi Asvin Mahersatillah Suradi Arham Arifin Arham Arifin Arwansyah Arwansyah Asmah Akhriana Erfan Hasmin Harlina, Sitti Heriadi Heriadi Imran Djafar Indra Samsie Komang Aryasa M. Syukri Mustafa Muhammad Rizal Muhammad Rizal Muhammad Rizal Muhammad Sabirin Hadis Muhammad Syukri Mustafa Mushaf Mushaf Mushaf Mushaf Novita Sambo Layuk Nurul Aini Samsu Alam Santi Santi Sitti Aisa SRI WAHYUNINGSIH PIU Sriwahyuningsi Piu Suci Ramadhani Arifin Sunardi Sunardi Wilem Musu Wilem Musu