Sentiment Analysis of Online Transporrtation Service Using The Naïve Bayes

Sentiment Analysis of Online Transporrtation Service Using The Naïve Bayes

• By M, Tika Adilah; Supendar, Hendra; Ningsih, Rahayu; Muryani, Sri; Solecha, Kusmayanti;
• Seminar Internasional Bereputasi
• 99
• 1-6

Sentiment analysis is a computational study of opinions and emotions expressed textually. Sentiment analysis will group text in sentences or documents to find out the opinions expressed in the sentence or document, whether negative or positive. This sentiment analysis research was conducted on the online taxi transportation service. Gojek uses a lot of social media to communicate with its customers, one of the social media used is Instagram. This research takes 1000 comments from the Instagram of the Gojek page which is used to see the public opinion of the online Gojek transportation services. Comments from the page are processed by doing text preprocessing and then classified using the Naive Bayes Classifier (NBC) method to obtain the value of the public value for online transportation services. The results of this study using the Naive Bayes method resulted in an accuracy value of 81.00%, which means that from all the comments on the Instagram page, the subject of the NBC method could be accurately classified by 81.00% whether the comments were negative or positive comments.

• Katakunci
• URL https://iopscience.iop.org/article/10.1088/1742-6596/1641/1/012093/pdf
• Penerbit Journal of Physics: Conference Series (IOP Science),

REFERENSI

[1] Giancristofaro G T and Panangadan A, 2016 Predicting Sentiment toward Transportation in Social Media using Visual and Textual Features IEEE Conf. Intell. Transp. Syst. Proceedings, ITSC p. 2113{2118.

[2] Hapsari Y Fikri Hidayattullah M Dairoh D and Khambali M, 2018 Opinion Mining Terhadap Toko Online Di Media Sosial Menggunakan Algoritma Na¨ıve Bayes (Studi Kasus: Akun Facebook Dugal Delivry) J. Inform. J. Pengemb. IT 3, 2 p. 233{236.

[3] Mailanto A, 2016, Pengguna Instagram di Indonesia Terbanyak, Mencapai 89%: Okezone techno.

[4] Wallsten S, 2015 The Competitive Effects of the Sharing Economy: How is Uber Changing Taxis? Technol. Policy Inst. June p. 1{22.

[5] Silalahi S L B Handayani P W and Munajat Q, 2017 Service Quality Analysis for Online TransportationServices: Case Study of GO-JEK Procedia Comput. Sci. 124 p. 487{495.

[6] Gojek, Tentang Kami | Gojek. [Online]. Available: https://www.gojek.com/about/. [Accessed: 27-Jun-2020].

[7] Shivaprasad T K and Shetty J, 2017 Sentiment analysis of product reviews: A review Proc. Int. Conf. Inven.Commun. Comput. Technol. ICICCT 2017 Icicct p. 298{303.

[8] Rosenthal S Farra N and Nakov P, 2018 SemEval-2017 Task 4: Sentiment Analysis in Twitter p. 502{518.

[9] Xhemali D Hinde C J and Stone R G, 2009 IJCSI IJCSI Na¨ıve Bayes vs. Decision Trees vs. Neural Networks in the Classification of Training Web Pages IJCSI Int. J. Comput. Sci. Issues 4, 1 p. 16{23.

[10] Dey L Chakraborty S Biswas A Bose B and Tiwari S, 2016 Sentiment Analysis of Review Datasets Using Na¨ıve Bayes‘ and K-NN Classifier Int. J. Inf. Eng. Electron. Bus. 8, 4 p. 54{62.

[11] Kristiyanti D A Umam A H Wahyudi M Amin R and Marlinda L, 2019 Comparison of SVM Na¨ıve Bayes Algorithm for Sentiment Analysis Toward West Java Governor Candidate Period 2018-2023 Based on Public Opinion on Twitter 2018 6th Int. Conf. Cyber IT Serv. Manag. CITSM 2018 Citsm p. 1{6.

[12] Elghazaly T Mahmoud A and Hefny H A, 2016 Political sentiment analysis using twitter data ACM Int. Conf. Proceeding Ser. 22-23-Marc.