SENTIMENT ANALYSIS TOWARDS THE YOGYAKARTA PALACE TOURISM OBJECT USING SUPPORT VECTOR MACHINE (SVM)

PRAKOSO, CAHYO (2024) SENTIMENT ANALYSIS TOWARDS THE YOGYAKARTA PALACE TOURISM OBJECT USING SUPPORT VECTOR MACHINE (SVM). Tugas Akhir thesis, Informatics.

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Abstract

ABSTRACT Tourist attractions have an important role in a region's tourism industry. Therefore, it is important to understand visitors' opinions and sentiments towards certain tourist attractions. In this context, this research aims to analyze visitor sentiment towards the Kraton Yogyakarta tourist attraction based on reviews found on the Google Maps platform. With a better understanding of visitor sentiment, stakeholders and attraction managers can take appropriate steps to improve the tourist experience. This research uses the Support Vector Machine (SVM) method in sentiment analysis. The SVM method is used to classify visitor reviews into positive and negative sentiment categories. The use of TF-IDF aims to give higher weight to important words in reviews. This combination of SVM and TF-IDF methods provides an effective approach for sentiment analysis based on visitor reviews. In this research, the performance of various SVM kernels was evaluated, and the results showed that the use of the sigmoid kernel provided the highest accuracy in classifying visitor sentiment at the Kraton Yogyakarta tourist attraction. In testing, SVM with a sigmoid kernel achieved an accuracy of 84.75%, with precision of 91.02%, recall of 88.14%, and f1-score of 89.56%. Keywords: Kraton, Review, Goggle Maps, Sentiment Analysis, Support Vector Machine

Item Type: Thesis (Skripsi, Tugas Akhir or Kerja Praktek) (Tugas Akhir)
Subjects: T Technology > T Technology (General)
Divisions: Fakultas Sains Dan Teknologi > S1 Informatika
Depositing User: Kaprodi S1 Informatika UTY
Date Deposited: 07 Aug 2024 01:19
Last Modified: 07 Aug 2024 01:19
URI: http://eprints.uty.ac.id/id/eprint/15797

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