PENERAPAN DEEP LEARNING UNTUK PREDIKSI KASUS AKTIF COVID-19

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

[thumbnail of Syafaah Lestandy -  Covid-19 Deep Learning prediction.pdf]
Preview
Text
Syafaah Lestandy - Covid-19 Deep Learning prediction.pdf

Download (896kB) | Preview
[thumbnail of Similarity - Syafaah Lestandy -  Covid-19 Deep Learning prediction.pdf]
Preview
Text
Similarity - Syafaah Lestandy - Covid-19 Deep Learning prediction.pdf

Download (1MB) | Preview

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
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

Actions (login required)

View Item
View Item