Sentiment Analysis of FLO Applications For Women's Needs Using The CNN And LSTM Algorithms.
DOI:
https://doi.org/10.59188/eduvest.v4i5.1182Keywords:
FLO, Sentiment, Convolutional Neural Network, Recurrent Neural Network, Long Short-Term MemoryAbstract
One application that helps women is an application that can track menstrual schedules, plan pregnancy and track pregnancy schedules until the estimated time of delivery. An example of an application that is widely used on the Google Play Store is FLO. FLO application that has been downloaded more than 100 million times and has been reviewed as many as 2 million reviews on the Google Play Store seen on January 12, 2023. Sentiment Analysis is an ongoing research field in the field of text mining and also the computational treatment of opinions, sentiments and subjectivity text that can be used as an evaluation of an application. The method chosen in this sentiment analysis research is CNN and RNN with Long Short Term Memory (LSTM) variants. In this study, the data used to carry out sentiment analysis is review data in text form. The results of sentiment analysis with the research object of FLO application reviews were 12,000 review data selected by country, namely Indonesia, which had more positive reviews, followed by neutral reviews and finally negative reviews. In the training data obtained, accuracy and loss by doing three epochs, namely 20, 50, 100 on the CNN and LSTM algorithms are good enough and not overfitting. Data testing is also carried out using confusion matrix and classification report, based on the two algorithm comparisons, the superior one is using the LSTM algorithm, with accuracy of 92.67% and 93% respectively, while the CNN accuracy results are 84.08% and 84% respectively.
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