In this paper, an efficient model for the Turkish language sentiment analysis has been introduced. As Turkish is an agglutinative language, which requires spatial processing, an efficient pre-processing model was also implemented and integrated as a part of the developed system. In addition, the Deep Convolutional Neural Networks (ConvNet) have been integrated to build an efficient system. Several experiments using the "Turkish movie reviews" dataset have been conducted, and it has been observed that the developed system has improved the sentiment analysis system that supports the Turkish language and significantly outperforms the existing state-of-the-art Turkish sentiment analysis systems.