Topic Modeling is a technique for unsupervised analysis of the large collection of the document. Topic model extracts the hidden topic from the large collection document. Topic Modeling Using Latent Dirichlet Allocation is document topic modeling system that extent the Latent Dirichlet Allocation. This model is applied to a collection of 18846 document from the 20 Newsgroups (Qwone.com, n.d.). But the model was tested on few newsgroup document .The model gives the latent hidden topics cluster which is visualized in the Pie chart along with the frequency of words appearing in the document. The output of the model is tested using the term coherence which shows that a good topic model is one that has higher value and gives topic with more human interpretable. The good model with 50 iterations and topic 2 value is -12.9647523036 and the bad topic with 1 iteration and topic 2 have the value of -14.9906055583