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 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.