Sentiment Analysis Using Backpropagation Method to Recognize the Public Opinion

Abstract

Improve the service quality of tourism actors by conducting sentiment analysis on digital platforms owned by tourism businesses and collecting negative sentiments to improve the quality of services from companies owned by tourism businesses. The growth of the hospitality industry in Indonesia is experiencing rapid growth every year. The tourism industry, part of the hospitality industry, also does not escape the influence of positive and negative sentiments. One method to perform accurate sentiment analysis is Backpropagation Neural Network. Based on the results of tests on the neural network, the best accuracy is obtained when using one hidden layer with the first layer of 10 neurons. The learning rate is 0.000002, where the accuracy is 71.630%. More epochs do not guarantee better accuracy. Based on the results of the research that has been done, suggestions for further researchers are to analyze the review dataset processing method so that it gets a cleaner dataset and is expected to improve better accuracy.

Keywords

• sentiment analysis
• neural network
• backpropagation