The economy is an aspect that is most susceptible to change. As a countermeasure to these changes, the government making efforts with a policy on using digital money. The digital money transaction tool issued by the Indonesian government is QRIS (Quick Response Code Indonesian Standard). However, the fact is that public interest in using QRIS is still low. This study aims to determine the factors that influence it significantly and obtain a model of the lack of public interest using QRIS, using the Bayesian logistic regression method. The Bayesian logistic regression method can generate parameter estimates by combining the likelihood function of the sample data with the prior distribution and the results are referred to as the posterior. In addition, the predictor variables used in this study are age, shopping frequency, consumer income, and the number of digital payment applications and for the response variable is a lack of interest in QRIS, for the sampling method used is accidental sampling and the sample used is primary data sourced from the results of filling out questionnaires distributed to consumer communities in Badung, Kreneng, and Galang Ayu Markets. Estimation from the Bayes method was obtained using a Markov Chain Monte Carlo (MCMC) simulation. The results of this study indicate that the variables of age and the number of digital payment applications have a significant effect on people's lack of interest in using QRIS
