ABSTRACT
Corona Virus Disease (Covid-19) has become the focus of world attention because it attacked many people in the world and many people died. The effect of Covid-19 is not only on the health of people, it is negatively affecting all aspects of life including the social area, economy, sport, and tourism. Hotels and restaurants that are an important part of the tourism industry have got a big negative impact from Covid-19. Since this disease has spreaded in many countries including Indonesia, the Indonesian goverment adopted regulations to close the hotels and restaurants to prevent the spread of Covid-19. This research comes from the need to find out the estimated number of hotels and restaurants to be closed due to Covid-19. The estimation method will involve the Backpropagation Neural Network. The Backpropagation Neural Network can make estimation of the number of closed hotels and restaurants approaching the target. Simulations are applied by splitting the dataset into training data (80%) and testing data (20%). From Backpropagation Neural Network simulations, the Backpropagation Neural Network can make estimation of the number of closed hotels and restaurants in training data with optimal RMSE being 9.2422 and testing data with optimal RMSE being 8.9419. © 2022 InforMath Publishing Group.
ABSTRACT
Corona virus disease (COVID-19) have become a world health problem because they have attacked many people worldwide. Because this virus has spread massively in almost all countries, including Indonesia, the Indonesian government made some policies and rules to close down the hotels and restaurants to avoid the spread of COVID-19. Because of that, estimation of the number of closed down restaurants and hotels in Jakarta is vital for avoiding COVID-19 spreads further to other people, either domestic or foreign. In this paper, the adaptive neuro-fuzzy inference system (ANFIS) is chosen as the estimation method. In estimating the number of closed restaurants and hotels using ANFIS, supporting variables such as the amount of casualties in Jakarta, the amount of casualties in Indonesia, and the amount of casualties in the world is required. As a result, ANFIS can estimate the amount of closed down restaurants and hotels approaching the target. The simulations are organized by partitioning the dataset into two parts: data of (80%) and data of testing (20%). According to ANFIS simulations, ANFIS can estimate the number of closed down restaurants and hotels in training data with optimal RMSE equals 0.5324 and testing data with optimal RMSE equals 5.3198. © 2022, Institute of Advanced Engineering and Science. All rights reserved.