How to create Random Forest from scratch in R (without the randomforest package)

This is the way I want to use Random Forest by using the RandomForest Package:

library (randomForest)
rf1 <- randomForest(CLA ~ ., dat, ntree=100, norm.votes=FALSE)
p1 <- predict(rf1, testing, type='response')
confMat_rf1 <- table(p1,testing_CLA$CLA)
accuracy_rf1 <- sum(diag(confMat_rf1))/sum(confMat_rf1)

I don't want to use the RandomForest Package at all. Given a dataset (dat) and using rpart and default values of randomforest package, how can I get the same results? For instance, for the 100 decision trees, I need to run the following:

for(i in 1:100){
cart.models[[i]]<-rpart(CLA~ ., data = random_dataset[[i]],cp=-1)
} 

Where each random_dataset[[i]] would be randomly chosen default number of attributes and rows. In addition, does rpart used for randomforest?