We proposed stacking ensemble model to solve the problem of feature-based opinion mining. We used Naive Bayes, Support Vector Machine and K-Nearest Neighbor as base learner and Support Vector Machine as Meta Classifier. Using domain knowledge the dataset consists of Feature-Opinion-Negation triple is created and trained using the proposed stacking ensemble model. The proposed model predicts feature based opinion polarity identification of 4096 laptop product reviews with 92.5315% accuracy.