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All Journal Building of Informatics, Technology and Science JUSTICE: Journal of Social and Political Science
Apriani, Linda
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Computer Science & IT Languange, Linguistic, Communication & Media Social Sciences

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Analisis Sentiment Terhadap Diabetes Menggunakan Algoritma Naïve Bayes, Random Forest, SVM Pada Media Sosial X Apriani, Linda; Hendrastuty, Nirwana
Building of Informatics, Technology and Science (BITS) Vol 6 No 4 (2025): March 2025
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v6i4.6941

Abstract

Diabetes is one of the chronic diseases that has received widespread attention in society, especially on social media X. This is due to the increasing number of sufferers every year. Based on data from the World Health Organization (WHO), in 2021 it is estimated that 537 million people aged 20-79 years are living with diabetes, an increase from the 2019 estimate of 463 million people. In addition, around 1.3 million deaths are caused by diabetes, with 4 percent of them occurring before the age of 70. This condition occurs due to high blood sugar levels that interfere with the body's metabolic functions, making it difficult for the body to process sugar optimally. This study aims to compare the performance of Naïve Bayes, Random Forest, and Support Vector Machine (SVM) algorithms in sentiment analysis related to diabetes. The research data was obtained from the Twitter platform with a total of 8,401 tweets collected using crawling techniques using certain keywords in the time span of 2024 to 2025. The data then went through a pre-processing stage to produce clean data. Tests were conducted to evaluate the accuracy of each model in predicting public sentiment. The test results show that the SVM algorithm provides the best performance with 85% accuracy, followed by Random Forest with 82% accuracy, and Naïve Bayes with 74% accuracy before the application of Synthetic Minority Oversampling Technique (SMOTE). After optimization using SMOTE, the SVM algorithm still showed the best performance with 96% accuracy, followed by Random Forest with 95% accuracy, and Naïve Bayes with 85% accuracy. Based on these results, SVM proved to be the most effective algorithm in classifying sentiment related to diabetes. It is hoped that the results of this research can contribute to efforts to manage diabetes through a better understanding of public perceptions.
Personal Branding Tokoh Ekonomi di Media Sosial: Studi Respons Audiens Atas Citra Purbaya Yudhi Sadewa di TikTok Satya Ananda, Muhammad Febiandri; Aisyah, Siti; Cristy, Maya; Apriani, Linda
JUSTICE: Journal of Social and Political Science Vol 5 No 1 (2026): JUSTICE: Journal of Social and Political Science
Publisher : JUSTICE Journal Of Social and Political Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51792/5fyyx721

Abstract

Personal branding di media sosial kini  banyak sekali dilakukan oleh tokoh ekonomi sebagai strategi komunikasi untuk membangun kepercayaan, kredibilitas dan mengambil hati masyarakat. Berbagai platform media sosial dimanfaatkan secara strategis oleh tokoh ekonomi untuk membentuk personal branding. Salah satunya, TikTok. Penelitian ini bertujuan menganalisis personal branding tokoh ekonomi di media sosial TikTok serta respons audiens terhadap citra yang dibangun, dengan fokus pada Purbaya Yudhi Sadewa. Penelitian menggunakan pendekatan kualitatif dengan metode deskriptif dan paradigma konstruktivisme. Data dikumpulkan melalui observasi terhadap konten video pada akun TikTok @purbayayudhis selama periode September 2025, serta pengamatan dan analisis terhadap respons audiens berupa komentar dan interaksi, serta studi literatur yang relevan dengan penelitian ini. Hasil penelitian menunjukkan bahwa Purbaya Yudhi Sadewa membangun personal branding sebagai tokoh ekonomi yang komunikatif, humanis, dan dekat dengan masyarakat melalui penyampaian pesan kebijakan yang sederhana dan mudah dipahami. Hal ini terbukti dengan komunikasi yang terjalin secara dua arah serta penerimaan positif dari masyarakat terhadap citra yang dibangun. Personal branding tersebut dibentuk secara konsisten melalui empat tahapan, yaitu determine who you are, determine what you do, position yourself, dan manage your brand. Respons audiens yang aktif menunjukkan terjadinya komunikasi dua arah. Penelitian ini menyimpulkan bahwa TikTok efektif dimanfaatkan sebagai media personal branding dan komunikasi publik tokoh ekonomi di era digital
Co-Authors Cristy, Maya Muhammad Febiandri Satya Ananda Nirwana Hendrastuty Siti Aisyah