Open AccessSentimen Analisis Terhadap Aplikasi pada Google Playstore Menggunakan Algoritma Naïve Bayes dan Algoritma Genetika
Author(s) -
Arif Rahman,
Ema Utami,
Sudarmawan Sudarmawan
Publication year - 2021
Publication title -
jurnal komtika (komputasi dan informatika)
Language(s) - English
Resource type - Journals
eISSN - 2580-734X
pISSN - 2580-2852
DOI - 10.31603/komtika.v5i1.5188
Subject(s) - overfitting , computer science , naive bayes classifier , sentiment analysis , artificial intelligence , bayes' theorem , product (mathematics) , genetic algorithm , bayesian probability , machine learning , data mining , mathematics , artificial neural network , support vector machine , geometry
Sentiment analysis is a science to extract text to get someone's emotions for that. The benefits of sentiment analysis have many benefits, one of which is to see whether or not customers have a good response to the product and this can be an input for the development of the product's business in the future. The weakness of previous studies in research sentiment analysis is that the authors conduct research to improve the results of previous studies using the naïve Bayes algorithm that is optimized with a genetic algorithm. From the results of the research that has been done, the average value in this study is on average better than previous studies, no applications have been identified as underfitting or overfitting and finally the naïve Bayes algorithm that has been optimized by the genetic algorithm can be a classification solution for sentiment analysis.