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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Jurnal Teknologi Informasi dan Ilmu Komputer Sistemasi: Jurnal Sistem Informasi JOIV : International Journal on Informatics Visualization Sinkron : Jurnal dan Penelitian Teknik Informatika SMARTICS Journal INTECOMS: Journal of Information Technology and Computer Science J-SAKTI (Jurnal Sains Komputer dan Informatika) Jusikom: Jurnal Sistem Informasi Ilmu Komputer Zonasi: Jurnal Sistem Informasi Buana Information Technology and Computer Sciences (BIT and CS) REMIK : Riset dan E-Jurnal Manajemen Informatika Komputer JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) JIKA (Jurnal Informatika) Jurnal Sistem Komputer dan Informatika (JSON) Infotek : Jurnal Informatika dan Teknologi Journal of Applied Data Sciences Jurnal Cahaya Mandalika Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer) Jurnal Pendidikan dan Teknologi Indonesia International Journal of Computer and Information System (IJCIS) Jurnal Informatika dan Teknologi Komputer ( J-ICOM) KLIK: Kajian Ilmiah Informatika dan Komputer J-SAKTI (Jurnal Sains Komputer dan Informatika) Journal of Informatics and Communication Technology (JICT) Malcom: Indonesian Journal of Machine Learning and Computer Science JUSIFOR : Jurnal Sistem Informasi dan Informatika Innovative: Journal Of Social Science Research Jurnal Sistem Informasi dan Manajemen VISA: Journal of Vision and Ideas INTERNAL (Information System Journal) Journal of Informatics and Communication Technology (JICT) IKRAM: Jurnal Ilmu Komputer Al Muslim
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Journal : SMARTICS Journal

Analisis Sentimen, Grab Indonesi Analisis Sentimen Grab Indonesia Pada Ulasan Google Play Store Menggunakan Algoritma Naïve Bayes Dan SVM Nurfauzi, Oka Muhamad; Hilabi, Shofa Shofiah; Nurapriani, Fitria; Huda, Baenil
SMARTICS Journal Vol 11 No 1 (2025): SMARTICS Journal (April 2025)
Publisher : Universitas PGRI Kanjuruhan Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21067/smartics.v11i1.11789

Abstract

This study uses the Naïve Bayes and Support Vector Machine (SVM) algorithms to analyze the sentiment of user reviews on the Grab Indonesia app on the Google Play Store.  Web scraping was used to gather the review data, which was then processed through a number of stages, such as tokenization, letter modification, the elimination of unnecessary words, and weighting using the TF-IDF approach.  The findings of the investigation demonstrate that SVM performs better in classifying positive and negative sentiments and has a greater accuracy (93%) than Naïve Bayes (92%).  But in terms of computational efficiency, Naïve Bayes continues to lead the field.  This study sheds light on how well both algorithms do sentiment analysis on Indonesian mobile apps