Making fake result in data mining using weka j48 algorithm
I don't understand the purpose when the quality of the tree is not important but you should be able to make a tree to have 100% accuracy on training data set easily. Just avoid any pruning and let the tree grow as maximum as possible. As far as I remember Weka set a pruning policy for J48 by default, you should disable that. Also check to see that the split nodes with minimum number of instances possible.

Now that I an considering better, there are cases when full accuracy is impossible. Think for example a simple toy data set with 10 instances. Suppose that all instances are the same for input variables, but for target variable 5 are positive and 5 are negative. Either way you take a decision for prediction, the accuracy on training data would be 0.5. In this case you simply do not have enough data to discriminate on.