Sentiment Analysis of English Hotel Reviews Using Support Vector Machine

SIMARMATA, ALEXANDER ROMIAN (2024) Sentiment Analysis of English Hotel Reviews Using Support Vector Machine. Tugas Akhir thesis, Informatics.

[img] Text
5200411345_Alexander Romian Simarmata_Abstrak.pdf
Download (11kB)

Abstract

ABSTRACT With the rapid emergence of technology in this decade, hotels can now receive hundreds or even thousands of reviews regarding their hotels. Of course, this is a task that takes a lot of time and energy if these reviews are read one by one. On the other hand, hotel reviews are very important for hotels in evaluating their performance in running the hotel business. In this research, an application will be created that uses sentiment analysis techniques, a text classification model to overcome this problem. The algorithm used in the research is Vector Machine (SVM). The hotel review data used as training data and test data for the model created will be downloaded via the Kaggle.com site. After that, the data will go through a preprocessing process which includes standardization, lemmatization, and creating labels on the data. After that the data will be divided into a ratio according to the user's wishes. The data that has been shared earlier will be implemented by the Support Vector Machine algorithm. This application was created in the Python programming language with the help of the SKLearn and Tkinter libraries. The result of this research is an application that can create a classification model using the SVM algorithm, and can manually classify hotel reviews in English and classify large numbers of hotel reviews in the form of .csv files. Keywords: Application, Sentiment Analysis, Hotel Reviews, 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: 09 Aug 2024 04:41
Last Modified: 09 Aug 2024 04:41
URI: http://eprints.uty.ac.id/id/eprint/15954

Actions (login required)

View Item View Item
UTY Open Access is powered by EPrints 3 which is developed by the School of Electronics and Computer Science at the University of Southampton. More information and software credits.