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Analisis Sentimen Pada Media Sosial X (Twitter) Terhadap Tumor Jinak Payudara Menggunakan Metode Naïve Bayes Lestari, Syntha Agung; Sugiyono
Jurnal Indonesia : Manajemen Informatika dan Komunikasi Vol. 5 No. 3 (2024): September
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Indonesia Banda Aceh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jimik.v5i3.1015

Abstract

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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