Sulastri, Sulastri and Eri, Zuliarso and Arief, Jananto PREDICTION OF THE DEVELOPMENT OF COVID-19 CASE IN INDONESIA BASED ON GOOGLE TREND ANALYSIS. Eduvest – Journal of Universal Studies.
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Abstract
The global outbreak of the coronavirus disease (COVID-19) has recently hit many countries around the world. Indonesia is one of the 10 most affected countries. Search engines such as Google provide data on search activity in a population, and this data may be useful for analyzing epidemics. Leveraging data mining methods on electronic resource data can provide better insights into the COVID-19 outbreak to manage health crises in every country and around the world. This study aims to predict the incidence of COVID-19 by utilizing data from the Covid 19 Task Force and the Google Trends website. Linear regression and long-term memory (LSTM) models were used to estimate the number of positive COVID-19 cases.
| Item Type: | Article |
|---|---|
| Subjects: | Q Science > Q Science (General) |
| Faculty / Institution: | Fakultas Teknologi Informasi |
| Depositing User: | Fakultas Ekonomi |
| Date Deposited: | 05 Jan 2023 06:50 |
| Last Modified: | 05 Jan 2023 06:50 |
| URI: | https://eprints.unisbank.ac.id/id/eprint/9053 |
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