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All Journal JSAI (Journal Scientific and Applied Informatics)
Giri Purnama
Fakultas Teknik dan Informatika, Universitas Dian Nusantara
Computer Science & IT

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Analisis Sentimen Ulasan Instagram Menggunakan Algoritma Support Vector Machine dan Random Forest (Studi Kasus: Universitas Dian Nusantara) Giri Purnama
JSAI (Journal Scientific and Applied Informatics) Vol 9 No 2 (2026): Juni
Publisher : Fakultas Teknik Universitas Muhammadiyah Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36085/jsai.v9i2.11045

Abstract

The increasing use of social media, particularly Instagram with over 1 billion active users in 2023, creates opportunities for Universitas Dian Nusantara (UNDIRA) to understand public perception through user review analysis. This study aims to develop a machine learning-based sentiment analysis model to categorize UNDIRA Instagram user reviews into positive, negative, and neutral sentiments. The novelty of this study lies in the combined use of TF-IDF and Word2Vec features together with a systematic comparison of SVM and Random Forest on Indonesian-language review data, a context still rarely examined for higher-education institutions. The research involved data collection through Instagram scraping, data preprocessing including stop word removal and stemming, and the application of three machine learning models: Support Vector Machine (SVM) with TF-IDF feature extraction, Random Forest (RF) with Word2Vec, and RF with TF-IDF. Results indicate that SVM with TF-IDF achieved the best performance with 99.11% accuracy and 99.13% F1-Score, outperforming Random Forest at 96.43% accuracy
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