Implementation Of K-Nearest Neighbor Algorithm With SMOTE For Hotel Reviews Sentiment Analysis
DOI:
10.33395/sinkron.v8i2.12214Keywords:
Hotel Review, K-Nearest Neighbor, Sentiment Analysis, SMOTE, TravelokaAbstract
Indonesia has considerable tourism development potential, this phenomenon is in accordance with the number of foreign tourist visits to Indonesia from January to September 2022 recorded by Badan Pusat Statistik many as 2,397,181 visitors. This research focuses on super-priority destinations in Labuan Bajo, East Nusa Tenggara, based on the government's plan that the focus of developing this destination is to increase hotel development to meet the need for an additional 2,000 hotel rooms. Thus, the available hotel rooms are still limited. Then for need to choose a hotel based on the November 2021 survey by the Populix website, 76% of 1,012 respondents chose to book hotels online with the majority using the Traveloka website. However, making decisions in choosing hotels using the reviews feature in the Traveloka website still raises various problems, such as biased information and even the rating values given do not match the reviews submitted. So that users to know what becomes the perception of positive and negative ratings, it is necessary to do in-depth research on satisfaction factors to find out positive and negative sentiments of hotel visitors. This study uses the k-nearest neighbor algorithm with SMOTE on the research objects of the three most popular hotels in Labuan Bajo. Data testing uses a value of k = 3 so that it produces an accuracy value of 87.71% - 93.47% with a maximum error tolerance of 12.29%. In addition, the performance of accuracy results is validated by the appropriate AUC value, namely the good classification category.
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Copyright (c) 2023 Firman Gazali Mahmud, Teguh Iman Hermanto, Imam Maruf Nugroho
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