Performance Improvement Using CNN for Sentiment Analysis

Moch. Ari Nasichuddin (Universitas Gadjah Mada)
Teguh Bharata Adji (Universitas Gadjah Mada)
Widyawan Widyawan (Universitas Gadjah Mada)

IJITEE (International Journal of Information Technology and Electrical Engineering)
Vol 2, No 1 (2018): March 2018

The approach using Deep Learning method provides great results in various field implementations, especially in the field of Sentiment Analysis. One of Deep Learning methods is CNN which has the ability to provide great accuracy in some previous research. However, there are some parts of the training process which can be improved to upgrade the accuracy level and the training time. In this paper, we try to improve the accuracy and processing time of sentiment analysis using CNN model. By tuning the filter size, frameworks, and pre-training, the results show that the use of smaller filter size and pre-training word2vec provide greater accuracy than some previous studies.