IMPLEMENTATION OF BACKPROPAGATION NEURAL NETWORK IN SENTIMENT ANALYSIS ON TWITTER TO PUBLIC FIGURES

Achmad Safruddin, Arief Hermawan, Adityo Permana Wibowo

Abstract

Sentiment analysis is a process for identifying or analyzing people's opinions on a topic. Sentiment analysis analyzes each word in a sentence to find out the opinions or sentiments expressed in the sentence. The opinions expressed can be in the form of positive or negative opinions. Twitter is one of the most popular social media in Indonesia. Twitter users always discuss various kinds of topics every day. One of the things discussed on Twitter and which has become a trending topic several times is about public figures. This study discusses the analysis of positive or negative sentiments towards public figures based on tweet data carried out by text processing. The results of text processing are classified using a backpropagation neural network. Tests were carried out using 69 test data, resulting in an accuracy of 62.3%, with 43 correct classification results.

Keywords

Sentiment Analysis, Public Figures, Backpropagation, Classification

References

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