During the COVID-19 pandemic, the public is urged to reduce the intensity of contact between people outside the home. Therefore, the government implemented Large-Scale Social Restrictions (PSBB) which caused many people to carry out activities only from home. This causes internet usage in Indonesia to continue to increase rapidly, one of which is because people choose to use food delivery services through applications. Online food delivery (OFD) is the process of ordering food through an application that can be done from anywhere and will be sent to our address according to the estimated time displayed by the application (Parmar, 2020). This research aims to determine the best hybrid model of customer satisfaction in using OFD and determine the most influence factor in customer satisfaction using OFD during the COVID-19 pandemic. Bayesian Network is an approach that uses a Directed Acyclic Graph (DAG) to represent the dependency relationship between random variables represented by nodes. The factors that affect customer satisfaction using OFD in this research are efficiency, system availability, privacy, fulfillment, perceived value, loyalty intention, price saving orientation and time saving orientation. Our findings reveal that the fulfillment is the most influencing factor on customer satisfaction in using OFD during the COVID-19 pandemic era with 0.1133 value of mutual information.

Keyword

Bayesian Network, Online Food Delivery, Sensitivity Analysis, COVID-19 Pandemic