Analisis sentimen K-popers terhadap dunia hiburan tanah air dengan algoritma Convolutional Neural Network (CNN)

Fhutuh, Irgiawan (2022) Analisis sentimen K-popers terhadap dunia hiburan tanah air dengan algoritma Convolutional Neural Network (CNN). Sarjana thesis, Universitas Islam Negri Sunan Gunung Djati.

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Abstract

Globalization that is currently happening has resulted in several changes in life, especially with the globalization of the media, the information spread in several countries becomes harmonious. This similarity of information creates a culture of information carriers. One of the cultures that is currently developing in Indonesia is pop culture or what we often hear with the term Korean Wave. The influence of Korean drama shows that attract the attention of the public, especially teenagers, causes imitation. Then the individual does so either liking it or not liking what he is doing that is happening. People become people who do not have characteristics because of uniformity. There is also conformity, which is a certain behavior that is carried out because of the influence of other people or groups to carry out the same behavior and actions. Sentiment analysis is very useful in monitoring social media because it can allow to gain insight and an overview of the wider public opinion behind a particular topic. It is a form of feeling or emotion, attitude or opinion. The use of the Convolutional Neural Network (CNN) Algorithm was chosen because it is considered better in overcoming Big Data and Machine Learning problems so that it can be developed to build a model to classify a word, sentence or paragraph. The process of classifying sentiments about k-popers towards the entertainment world with data obtained from Twitter, then pre-processing and weighting Word2Vec. Based on the results of the training experiments carried out, the best accuracy obtained was 85% for data from the entertainment world and 66% for k-pop.

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