Performance Improvement Using CNN for Sentiment Analysis

Moch. Ari Nasichuddin; Teguh Bharata Adji; Widyawan Widyawan

doi:10.22146/ijitee.36642

Performance Improvement Using CNN for Sentiment Analysis

https://doi.org/10.22146/ijitee.36642

Moch. Ari Nasichuddin^(1*), Teguh Bharata Adji⁽²⁾, Widyawan Widyawan⁽³⁾

(1) Universitas Gadjah Mada
(2) Universitas Gadjah Mada
(3) Universitas Gadjah Mada
(*) Corresponding Author

Abstract

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.

Keywords

CNN, Deep Learning, Sentiment Analysis

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DOI: https://doi.org/10.22146/ijitee.36642