THE PERCEPTIONS OF SEMARANG FIVE STAR HOTEL TOURISTS WITH SUPPORT VECTOR MACHINE ON GOOGLE REVIEWS

Muhammad Haikal Aufan; Maya Rini Handayani; Afifah Basmah Nurjanna; Nur Cahyo Hendro Wibowo; Khotibul Umam

doi:10.52436/1.jutif.2024.5.5.2025

Muhammad Haikal Aufan Department of Information Technology, Science and Technology Faculty, Universitas Islam Negeri Walisongo Semarang, Indonesia
Maya Rini Handayani Department of Da'wah and Communication, Science and Technology Faculty, Universitas Islam Negeri Walisongo Semarang, Indonesia
Afifah Basmah Nurjanna Department of Information Technology, Science and Technology Faculty, Universitas Islam Negeri Walisongo Semarang, Indonesia
Nur Cahyo Hendro Wibowo Department of Information Technology, Science and Technology Faculty, Universitas Islam Negeri Walisongo Semarang, Indonesia
Khotibul Umam Department of Information Technology, Science and Technology Faculty, Universitas Islam Negeri Walisongo Semarang, Indonesia

DOI: https://doi.org/10.52436/1.jutif.2024.5.5.2025

Keywords: 5-star hotel, Semarang, SVM

Abstract

Travelers on the road sometimes need a hotel to rest. In choosing a hotel, they refer to the ratings or reviews written by users through reviews on Google. This is because not all star hotels provide facilities in accordance with user assessments. This study discusses the analysis of the opinions of tourists who have stayed in 5-star hotels in Semarang through a review of commentary data on Google. The 5-star hotels used as the research are Padma, Gumaya, Tentrem, Grand Candi, Ciputra, and PO. The dataset of the six hotels was obtained through a scraping process then followed by data pre-processing. The data was retrieved from Google Maps using the Chrome Instant Data Scrapper extension. Data preprocessing begins with case folding, tokenizing, filtering, and ends with stemming. Support Vector Machine (SVM) is implemented for sentimen classification process. The results from this study are the majority of 5-star hotel reviews in Semarang tend to have positive rather than negative sentimens. Our model was able to produce an accuracy of 0.87 to 0.98. The highest accuracy was achieved by Ciputra Hotel at 0.98 with 543 positive reviews.

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