Using a logistic regression model calculated, create a classifier based on a suitable cut-off value in R [closed]

I have created a logistic regression model using the built in iris dataset in R...

# Includes iris dataset.
library(datasets)

# Dummy variable to predict.
iris$dummy.virginica.iris <- 0
iris$dummy.virginica.iris[iris$Species == 'virginica'] <- 1
iris$dummy.virginica.iris

# Logistic regression model.
glmfit<-glm(dummy.virginica.iris ~ Petal.Width, 
        data = iris, 
        family = 'binomial') 
summary(glmfit)

How would I create a classifier based on this model with a suitable cut-off value such as 0.5? Any suggestions or help would be greatly appreciated.