Analisis Sentimen Pada Media Sosial X (Twitter) Terhadap Tumor Jinak Payudara Menggunakan Metode Naïve Bayes
DOI:
https://doi.org/10.35870/jimik.v5i3.1015Keywords:
Sentiment Analysis, Benign Breast Tumors, Twitter (X), Naïve BayesAbstract
Benign breast tumors are a medical condition that often raises concerns among the public. This research aims to analyze public sentiment towards benign breast tumors via social media Twitter (X) using the Naïve Bayes algorithm. Data was collected from tweets containing keywords related to benign breast tumors within a certain time period. After data pre-processing, including text cleaning and duplication removal, the data was then classified into positive and negative sentiments using the Naïve Bayes algorithm. This research provides insight into public perceptions of benign breast tumors on social media, and emphasizes the importance of more in-depth health education and disseminating accurate information about the condition. It is hoped that the results of this research can become a reference for health practitioners and policy makers in designing more effective health communication strategies.
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