Prediction of COVID-19 Using the Artificial Neural Network (ANN) with K-Fold Cross-Validation

Background: COVID-19 is a disease that attacks the respiratory system and highly contagious, so cases of spread are increasing every day. The increase in cannot be predicted accurately, resulting shortage services, facilities medical personnel. This number will always if community not vigilant actively reduces rate adding confirmed cases. Therefore, public awareness vigilance need to increased by presenting information on predictions cases, recovered death it can used as reference for government taking establishing policy overcome COVID-19. Objective: research predicts Lampung Province Method: study uses ANN method determine best network architecture predicting deaths from using k-fold cross-validation measure predictive model performance. Results: has good ability with an accuracy value 98.22% 98.08% cured 99.05% Conclusion: predict decreased October 27, 2021, January 24, 2022. Keywords: Artificial Intelligence, Neural Network (ANN) K-Fold Cross Validation, Cases, Data Mining, Prediction.