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All Journal Pendas : Jurnah Ilmiah Pendidikan Dasar JSAI (Journal Scientific and Applied Informatics) Journal of Community Development and Disaster Management MACHINERY: Jurnal Teknologi Terapan
Ardi, Ardiansyah
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Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Energy Environmental Science Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mechanical Engineering Social Sciences Other

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Journal : JSAI (Journal Scientific and Applied Informatics)

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Optimasi Metode Naïve Bayes Classifier Menggunakan Pendekatan Term Frequency-Inverse Document Frequency (TF-IDF) Pada Analisis Sentimen Ardi, Ardiansyah; Kurniawan
JSAI (Journal Scientific and Applied Informatics) Vol 7 No 3 (2024): November
Publisher : Fakultas Teknik Universitas Muhammadiyah Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36085/jsai.v7i3.7153

Abstract

The main objective of this research is to conduct an analysis of public sentiment directed toward RSUD Siti Fatimah, using the Naïve Bayes Classifier methodology. This analytical approach was used to systematically categorize reviews into positive and negative sentiments. Data relating to the reviews was obtained through web scraping techniques from Google Maps, followed by a series of text preprocessing procedures, which included text sanitization, tokenization, and the application of TF-IDF for weighting. Based on the positive Classification values Precision shows 83%, Recal 1.00, and F-1 Score 0.91 which means the Model shows excellent performance in identifying positive sentiments. However, the model is less effective in identifying negative sentiments, with very low recall.
Co-Authors Eko Saputra Kiranti Pratiwi Kurniawan Ramadani Irja Pangestu Rizki Ananda Yunus, Muhhammad Zamheri, Ahmad Zira Lestari