Perbandingan Kinerja Metode Random Forest dan Naive Bayes Untuk Analisis Sentiment Masyarakat Terhadap Childfre pada Twitter. (Performance comparison of Random Forest and Naïve Bayes methods for public sentiment analysis of Childfree on Twitter).

Irianto, Giwa Salsabila Ferari (2023) Perbandingan Kinerja Metode Random Forest dan Naive Bayes Untuk Analisis Sentiment Masyarakat Terhadap Childfre pada Twitter. (Performance comparison of Random Forest and Naïve Bayes methods for public sentiment analysis of Childfree on Twitter). Undergraduate thesis, Universitas 17 Agustus 1945 Surabaya.

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Abstract

The phenomenon of childfree began to become a concept of marriage for society when husbands and wives choose and commit not to have children in their marriage. Factors for the emergence of this phenomenon are economic factors, mental unpreparedness in nurturing and raising children, the level of busyness of married couples and even issues of social environmental problems. The childfree phenomenon still reaps pros and cons because of differences in opinions and points of view regarding the presence of children in marriage. The pros and cons of this phenomenon can be seen on social media Twitter. The focus of this study is on sentiment analysis of people's views on childfree on Twitter, using Random Forest and Naïve Bayes analysis methods. In obtaining data on public sentiment towards childfree on Twitter social media, this study was conducted using scrapping techniques in the form of tweets from Indonesian people about childfree, besides that the tweets contained Indonesian. Based on the data collection, 1309 tweets were obtained. The evaluation results showed that Random Forest had a higher accuracy rate (81.85%) compared to Naïve Bayes (78.75%) when Tagger Post was used. However, without Post Tagger, Naïve Bayes achieved higher accuracy (69.72%) than Random Forest (67.33%). The study provides insight into societal responses to the childfree phenomenon and a comparison of the performance of two sentiment analysis methods.

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