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All Journal TEKNOSIA
Deni Ramadhan
Jurusan Teknologi Informasi, Politeknik Negeri Padang
Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Engineering Transportation

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STUDI BIBLIOMETRIK: PENERAPAN ALGORITMA SUPPORT VECTOR MACHINE DALAM ANALISIS SENTIMEN BERBASIS WEB UNTUK KEPUASAN PELANGGAN Deni Ramadhan; Defni; Rostam Ahmad Efendi; Yulherniwati
Teknosia Vol. 20 No. 1 (2026): Vol. 20 No. 01 (2026): June 2026
Publisher : UNIB Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33369/teknosia.v20i1.49393

Abstract

In the digital business era, customer satisfaction is a critical metric often evaluated through internet-based sentiment analysis, where Support Vector Machine (SVM) has emerged as a highly reliable algorithm. This study aims to map existing literature and identify future trends regarding the application of SVM in analyzing online sentiment for customer satisfaction. A bibliometric analysis was conducted using literature metadata from leading databases, with citation and trend analyses visualized via VOSviewer. Our network visualizations reveal key thematic clusters, highlighting a strong correlation between the SVM algorithm and the evaluation of customer reviews. Furthermore, density visualizations successfully identify specific research gaps, particularly concerning the integration of SVM with web-based platforms. These findings offer clear directions for future research. While the foundational applications of SVM have been extensively studied, exploring web-based data approaches still presents significant opportunities for future investigation.
Co-Authors Defni Rostam Ahmad Efendi Yulherniwati