Polynomial Regression Method and Support Vector Machine Method for Predicting Disease Covid-19 in Indonesia

Bambang Purnomosidi Dwi Putranto (Master of Information Technology, Universitas Teknologi Digital Indonesia)
Moh. Abdul Kholik (Master of Information Technology Universitas Teknologi Digital Indonesia)
Muhammad Agung Nugroho (Universitas Teknologi Digital Indonesia)
Danny Kriestanto (Universitas Teknologi Digital Indonesia)

Journal of Intelligent Software Systems
Vol 2, No 1 (2023): July

The COVID-19 pandemic has become a major threat to the entire country. According to the WHO report, COVID-19 is a severe acute respiratory syndrome transmitted through respiratory droplets resulting from direct contact with patients. This study of data history is then processed using data mining prediction methods, namely the Polynomial Regression method compared to the Support Vector Machine method. Of the two methods will be sought the most accurate method by testing accuracy with MAE, MSE, and also MAPE to get the results of covid-19 predictions in Indonesia. Based on the comparison of test results through various scenarios against both methods, the Polynomial Regression method obtained the smallest test value, resulting in an accuracy value of MAE = 4146.025749867596, MSE = 19031800.02642069, MAPE = 0.006174164877416524. Polynomial regression is the best-recommended method