Analisis Sentimen Pada Agen Perjalanan Online Menggunakan Naïve Bayes dan K-Nearest Neighbor

  • Eka Wahyu Sholeha Politeknik Tanah Laut
  • Selviana Yunita Universitas Darwan Ali
  • Rifqi Hammad Universitas Bumigora
  • Veny Cahya Hardita STMIK Palangka Raya
  • Kaharuddin Kaharuddin Universitas Universal
Keywords: Sentiment Analysis, Online Travel Agent, Naive Bayes, K-Nearest Neighbor

Abstract

Social media has impact for decision maker to get more insights broadly. Including for online travel agent company, where costumer’s interest to use online travel agent for their chosen agent will grows along with the high number of customer’s satisfaction. As a one of the most important point in distribution, company provides a platform that reliable and effective to purchase a trip and share information of their experience through Online travel agent. It is important to know how consumer considerate which one the online travel agent they choose. One of their method is looking at the reviews. Facebook is one of social media that provide numerous reviews through comments sections. The research purposes are twofold, algorithm comparison and reveal the effect of uppercase as well as punctuation mark. The accuracy comparison between Naïve Bayes and K-Nearest Neighbor is provided against the datasets. This research collects the data from user comments on Facebook about the biggest three online travel agents in Indonesia. We classify the comments into three categories which are positive, negative, and neutral. The result of this research is found that K-Nearest Neighbor have slightly higher accuracy than the Naïve Bayes. Moreover, lowercase text without punctuation achieves better accuracy for both of algorithm. 

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Published
2022-01-25
How to Cite
Sholeha, E. W., Yunita, S., Hammad, R., Hardita, V. C., & Kaharuddin, K. (2022). Analisis Sentimen Pada Agen Perjalanan Online Menggunakan Naïve Bayes dan K-Nearest Neighbor . JTIM : Jurnal Teknologi Informasi Dan Multimedia, 3(4), 203-208. https://doi.org/10.35746/jtim.v3i4.178
Section
Articles

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