STUDI BIBLIOMETRIK: PENERAPAN ALGORITMA SUPPORT VECTOR MACHINE DALAM ANALISIS SENTIMEN BERBASIS WEB UNTUK KEPUASAN PELANGGAN

Deni Ramadhan (Jurusan Teknologi Informasi, Politeknik Negeri Padang)
Defni (Jurusan Teknologi Informasi, Politeknik Negeri Padang)
Rostam Ahmad Efendi (Jurusan Teknologi Informasi, Politeknik Negeri Padang)
Yulherniwati (Jurusan Teknologi Informasi, Politeknik Negeri Padang)

TEKNOSIA
Vol. 20 No. 1 (2026): Vol. 20 No. 01 (2026): June 2026

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.