Penerapan Support Vector Machine untuk Analisis Sentimen pada Google Review Hotel
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Harfin Ibna Pratama
*
Universitas Mercu Buana Yogyakarta, Sleman,
Indonesia
- Putri Taqwa Prasetyaningrum Universitas Mercu Buana Yogyakarta, Sleman, Indonesia (*) Corresponding Author
Abstract
This research aims to analyse customer sentiment towards Grand Rohan Hotel Yogyakarta using Google Reviews. Thus it can be a reference for hotel management to record customer reviews from internet users. Data was collected from user reviews during the period January to September 2024 in the form of 421 data. This research uses the Support Vector Machine (SVM) method to classify sentiment into positive and negative categories. The analysis process includes data collection using web scraping, data cleaning, text weighting using TF-IDF, and visualisation of analysis results. The results show that the SVM method is effective in analysing sentiment with an accuracy rate of 95%. Data visualisation through word clouds and pie charts provides additional insights for hotel management to improve service quality based on customer opinions. This research is implemented in a web application for real-time sentiment monitoring.
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