Comparison of Arima Model with The Addition of Linear Quadratic Estimation Algorithm for Prediction The Spread of Covid-19 in Kotabaru District

Eka Setya Wijaya (Universitas Lambung Mangkurat)
Bara Nugraha Putra Suryana

JTIULM (Jurnal Teknologi Informasi Universitas Lambung Mangkurat)
Vol. 9 No. 2 (2024)

Coronavirus disease 2019 (Covid-19) has been declared by WHO as a pro-longed global pandemic which has caused signif- icant public health problems, deaths and economic losses, therefore it is necessary to carry out prevention and control ef- forts to break the chain of transmission of Covid-19. One effort that can be done is to estimate the additional number of posi- tive cases of Covid-19, so that the number of isolation rooms and the need for medical personnel can be estimated. In this study the prediction of an increase in the number of positive cases of Covid-19 was carried out using the Linear Quadratic Estimation (Kalman Filter) approach based on the state space model formed from the ARIMA model (0,1,4). Based on train- ing data from March 23, 2020 to April 4, 2023, the best time series model is the ARIMA model (0,1,4) which was chosen based on the smallest AIC value and satisfies the residual test hypothesis