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All Journal SINTECH (Science and Information Technology) Journal
Setyaning Nastiti, Vina Rahmayanti
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Computer Science & IT

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Prediksi Jumlah Pasien Covid-19 Dengan Menggunakan Klasifikasi Algoritma Machine Learning Aidia, Aidia Khoiriyah Firdausy; Amelia, Putri Juli; Setyaning Nastiti, Vina Rahmayanti
SINTECH (Science and Information Technology) Journal Vol. 5 No. 2 (2022): SINTECH Journal Edition Oktober 2022
Publisher : Prahasta Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31598/sintechjournal.v5i2.1163

Abstract

Corona virus or servere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a disease that results in the occurrence of mild to moderate respiratory tract infections. Positive cases of Covid-19 in Indonesia were first detected on March 2, 2020 and continue until 2022. The additional number of deaths caused by COVID-19 has also increased. Therefore, the author is interested in making a predictive model of the cumulative number of COVID-19 patients who died in Indonesia. Therefore, in this study is how to predict the number of patients who die from COVID-19 in Indonesia by creating an appropriate accuracy model to help estimate the number of deaths associated with COVID-19 in Indonesia and assist the government in dealing with cases of new variants of COVID-19. In this study, the authors used the Decision Tree model  using entropy criteria as well as Information Gain and Random Forest which resulted in accuracy rates of 91.83% (Decission Tree) and 73.80% (Random Forest). The results, explain that the model used is good. The more the R-squared error value is close to 1, the better the model used will be
Co-Authors Aidia, Aidia Khoiriyah Firdausy Amelia, Putri Juli