Prediksi Tingkat Kesembuhan Pasien Covid-19 Berdasarkan Riwayat Vaksin Menggunakan Metode Naïve Bayes


  • Candra Gudiato * Mail Universitas Kristen Satya Wacana, Salatiga, Indonesia
  • Sri Yulianto Joko Prasetyo Universitas Kristen Satya Wacana, Salatiga, Indonesia
  • Hindriyanto Dwi Purnomo Universitas Kristen Satya Wacana, Salatiga, Indonesia
  • (*) Corresponding Author
Keywords: Covid-19; Vaccine; Data Mining; Naive bayes; Prediction

Abstract

Covid-19 has shocked the world since it first appeared at the end of December 2019. At the beginning of 2022, the global community is more prepared to face the COVID-19 pandemic, especially with the mass vaccination program in countries around the world, including Indonesia. The next issue is how effective the vaccine is in dealing with the COVID-19 virus. The main parameter used is to see the recovery rate of patients affected by COVID-19 based on the history of vaccine doses that have been received by the patient. In this study using data mining techniques, namely using the Naïve Bayes algorithm. The test results show the accuracy of the Naïve Bayes algorithm is 98.14%. The prediction results show that the recovery rate of patients who have received the vaccine, either dose 1, dose 2, or dose 3 (booster) is higher than those who have not been vaccinated at all (dose 0). The results of this study are expected to provide an overview to the public and the government about the benefits of vaccination in dealing with the Covid-19 virus.

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Article History
Submitted: 2022-06-24
Published: 2022-06-30
Abstract View: 116 times
PDF Download: 109 times
How to Cite
Gudiato, C., Prasetyo, S., & Purnomo, H. (2022). Prediksi Tingkat Kesembuhan Pasien Covid-19 Berdasarkan Riwayat Vaksin Menggunakan Metode Naïve Bayes. Building of Informatics, Technology and Science (BITS), 4(1), 191−199. https://doi.org/10.47065/bits.v4i1.1756
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