Prediction of the Development of Covid-19 Case in Indonesia Based on Google Trend Analysis

Autori

  • Sulastri Sulastri Universitas Stikubank (Unisbank) Semarang
  • Eri Zuliarso Universitas Stikubank (Unisbank) Semarang
  • Arief Jananto Universitas Stikubank (Unisbank) Semarang

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https://doi.org/10.59188/eduvest.v2i7.530

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Covid-19##common.commaListSeparator## Long ShortTerm Memori##common.commaListSeparator## Google Trend

Abstrakt

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.

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Publikované

2022-07-20