Sentiment analysis of restaurant reviews in Kuala Terengganu based on K-Nearest Neighbor/ Siti Syazwana Jafri

Sentiment analysis nowadays being the important role in many of industries that especially for the things or works that related to the review or feedback from the individual in the cyberspace. The people may review for the places, products and other things by expressing their emotion or opinions int...

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Main Author:	Jafri, Siti Syazwana
Format:	Thesis
Language:	English
Published:	2021
Subjects:	Instruments and machines Algorithms Database management
Online Access:	https://ir.uitm.edu.my/id/eprint/55650/1/55650.pdf
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id	my-uitm-ir.55650
record_format	uketd_dc
spelling	my-uitm-ir.556502023-12-12T02:06:00Z Sentiment analysis of restaurant reviews in Kuala Terengganu based on K-Nearest Neighbor/ Siti Syazwana Jafri 2021-02 Jafri, Siti Syazwana Instruments and machines Electronic Computers. Computer Science Algorithms Database management Sentiment analysis nowadays being the important role in many of industries that especially for the things or works that related to the review or feedback from the individual in the cyberspace. The people may review for the places, products and other things by expressing their emotion or opinions into a sentence. This action may lead to the problem of the understanding the meaning or description behind the texts and it also difficult to discover the sentunent polarity of the certain words. Some of the restaurant in Kuala Terengganu may be lacks in the term of the promotional the restaurants and any related activities often overlooked the reviews from the customers about the many different aspects of the restaurant. However, negative reviews will be affected the image of the restaurants. This study will perform the sentiment analysis on the restaurant reviews in Kuala Terengganu on the TripAdvisor. The study will be identified sentiment analysis tasks based on the classification model. A classifier will be designed and developed which is K- Nearest Neighbor (KNN). Lastly, the accuracy of die proposed classifier will be tested. The chosen technique is classification and the algorithm that will be applied in the classification process is K- Nearest Neighbor (KNN). The output will be the accuracy of the KNN model and the visualization of sentiment analysis of the new data that user will choose in the prototype. The accuracy achieved is 83%. In the future, it is very recommended to experiment with different algorithm. The volume of data should be large as it can generate better result of classification method. 2021-02 Thesis https://ir.uitm.edu.my/id/eprint/55650/ https://ir.uitm.edu.my/id/eprint/55650/1/55650.pdf text en public degree Universiti Teknologi MARA, Terengganu Faculty of Computer and Mathematical Sciences Mohd Sabri, Norlina
institution	Universiti Teknologi MARA
collection	UiTM Institutional Repository
language	English
advisor	Mohd Sabri, Norlina
topic	Instruments and machines Instruments and machines Algorithms Database management
spellingShingle	Instruments and machines Instruments and machines Algorithms Database management Jafri, Siti Syazwana Sentiment analysis of restaurant reviews in Kuala Terengganu based on K-Nearest Neighbor/ Siti Syazwana Jafri
description	Sentiment analysis nowadays being the important role in many of industries that especially for the things or works that related to the review or feedback from the individual in the cyberspace. The people may review for the places, products and other things by expressing their emotion or opinions into a sentence. This action may lead to the problem of the understanding the meaning or description behind the texts and it also difficult to discover the sentunent polarity of the certain words. Some of the restaurant in Kuala Terengganu may be lacks in the term of the promotional the restaurants and any related activities often overlooked the reviews from the customers about the many different aspects of the restaurant. However, negative reviews will be affected the image of the restaurants. This study will perform the sentiment analysis on the restaurant reviews in Kuala Terengganu on the TripAdvisor. The study will be identified sentiment analysis tasks based on the classification model. A classifier will be designed and developed which is K- Nearest Neighbor (KNN). Lastly, the accuracy of die proposed classifier will be tested. The chosen technique is classification and the algorithm that will be applied in the classification process is K- Nearest Neighbor (KNN). The output will be the accuracy of the KNN model and the visualization of sentiment analysis of the new data that user will choose in the prototype. The accuracy achieved is 83%. In the future, it is very recommended to experiment with different algorithm. The volume of data should be large as it can generate better result of classification method.
format	Thesis
qualification_level	Bachelor degree
author	Jafri, Siti Syazwana
author_facet	Jafri, Siti Syazwana
author_sort	Jafri, Siti Syazwana
title	Sentiment analysis of restaurant reviews in Kuala Terengganu based on K-Nearest Neighbor/ Siti Syazwana Jafri
title_short	Sentiment analysis of restaurant reviews in Kuala Terengganu based on K-Nearest Neighbor/ Siti Syazwana Jafri
title_full	Sentiment analysis of restaurant reviews in Kuala Terengganu based on K-Nearest Neighbor/ Siti Syazwana Jafri
title_fullStr	Sentiment analysis of restaurant reviews in Kuala Terengganu based on K-Nearest Neighbor/ Siti Syazwana Jafri
title_full_unstemmed	Sentiment analysis of restaurant reviews in Kuala Terengganu based on K-Nearest Neighbor/ Siti Syazwana Jafri
title_sort	sentiment analysis of restaurant reviews in kuala terengganu based on k-nearest neighbor/ siti syazwana jafri
granting_institution	Universiti Teknologi MARA, Terengganu
granting_department	Faculty of Computer and Mathematical Sciences
publishDate	2021
url	https://ir.uitm.edu.my/id/eprint/55650/1/55650.pdf
_version_	1794191830929113088

Sentiment analysis of restaurant reviews in Kuala Terengganu based on K-Nearest Neighbor/ Siti Syazwana Jafri

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