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Analysis Of User Satisfaction Sentiments On The Quality Of Website PT. Pertamina Uses Naive Bayes And Support Vector Machine Methods
Syadza Azzahra Nabilah (a), Sfenrianto (b), Dewi Ayu Puspitawati (a*), Abdussomad (a), Frieyadie (a), Cep Adiwihardja (c)

Sekolah Tinggi Manajemen Informatika dan Komputer Nusa Mandiri (a)
Jl. Damai No.8 Warung Jati Barat (Margasatwa) Jakarta Selatan DKI Jakarta, Telp. (021-78839502)
* dewiayu.puspitawati[at]gmail.com

Information Systems Management Department, BINUS Graduate Program (b)
Master of Information Systems Management, Bina Nusantara University, DKI Jakarta 11480

Universitas Bina Sarana Informatika (c)
Jl. Kamal Raya No.18, RT6/RW.3, Ringroad Barat, Cengkareng, Kota Jakarta Barat DKI Jakarta 11730


Abstract

Website managers are required to have the ability to manage, organize, and design the website so that users feel comfortable when searching for information on the website that has been made. Likewise with PT. Pertamina is making the companys website a place for promotion and providing information to users. The performance of a website can be increased as much as possible by analyzing and evaluating the level of satisfaction of its users. The public can assess a company by looking at how the company publishes information accurately with a view that is easily understood by the user. Ratings given are usually shared into various statuses on social media owned by users such as Twitter. On Twitter everyone makes a tweet, whatever the type of tweet that only consists of fragments of words whose meaning is difficult to know. The data is getting more and more and not systematically developed, from the existing problems a method is needed to classify a tweet from Twitter into a new knowledge using the Naive Bayes classification method and Support Vector Machine. After testing, the results showed that the SVM method produced an accuracy of 89.39% while the NB method produced an accuracy of 88.02%.

Keywords: Data Mining, Text Mining, Sentiment Analysis, Support Vector Machine, Naive Bayes

Topic: International Symposium of Engineering, Technology, and Health Sciences

Link: https://ifory.id/abstract/rtHGpxUQzb9T

Conference: The 3rd International Conference on Sustainability and Innovation (ICoSI 2019)

Plain Format | Corresponding Author (Dewi Ayu Puspitawati)

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