Syafaah, Lailis and Lestandy, Merinda (2021) PENERAPAN DEEP LEARNING UNTUK PREDIKSI KASUS AKTIF COVID-19. Jurnal Sains Komputer & Informatika (J-SAKTI), 5 (1). ISSN ISSN:2548-9771/EISSN:2549-7200
Syafaah Lestandy - Covid-19 Deep Learning prediction.pdf
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Abstract
Coronavirus disease (Covid-19) is increasingly spreading in Indonesia, so it requires an approach to predict its spread. One approach method that is often used is the Deep Learning (DL) method. DL is a branch of Machine Learning (ML) which is modeled based on the human nervous system. In this study, the prediction of active Covid-19 cases was resolved using the DL method. The dataset used is 260 data with 10 parameters. DL is able to provide an accurate prediction of active cases of Covid-19 with an MSE of 0.032 and an accuracy of 81.333%.
Item Type: | Article |
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Keywords: | Covid-19 Deep Learning prediction |
Subjects: | T Technology > TK Electrical engineering. Electronics Nuclear engineering |
Divisions: | Faculty of Engineering > Department of Electrical Engineering (20201) |
Depositing User: | evalina Risqi Evalina ST. |
Date Deposited: | 14 Mar 2024 04:17 |
Last Modified: | 14 Mar 2024 04:17 |
URI: | https://eprints.umm.ac.id/id/eprint/4742 |