How to further improve the kaggle titanic submission accuracy?
big question.

Ok so here's a few things I'd look at if I was you..


Have you tried any feature engineering ?(it sounds like you've just used the features in the training set but I can't be 100%)
Random Forests should do pretty well, but maybe try xgboost too? It's quite good at everything on Kaggle. SVM's could be worth a go also if you're thinking of stacking/ensembling.
Check out some of the tutorials around this competition. There's hundreds of them and most of them are great.


Links:

R #1 (my favourite)

R #2

Python #1

Python #2

...Hopefully this helps