Analisis Sentimen Review Restoran Di Situs Microblog Twitter Menggunakan Algoritma Support Vector Machine

• Main Author: Moehammad Aldin, (Author)
• Format: Book
• Published: 2020-07-27.
• Subjects: Thesis; NonPeerReviewed
• Online Access: Link Metadata
• Notes: http://repository.upnvj.ac.id/6535/12/ABSTRAK.pdf; http://repository.upnvj.ac.id/6535/13/AWAL.pdf; http://repository.upnvj.ac.id/6535/14/BAB%201.pdf; http://repository.upnvj.ac.id/6535/15/BAB%202.pdf; http://repository.upnvj.ac.id/6535/35/BAB%203.pdf; http://repository.upnvj.ac.id/6535/17/BAB%204.pdf; http://repository.upnvj.ac.id/6535/18/BAB%205.pdf; http://repository.upnvj.ac.id/6535/19/DAFTAR%20PUSTAKA.pdf; http://repository.upnvj.ac.id/6535/20/RIWAYAT%20HIDUP.pdf; http://repository.upnvj.ac.id/6535/21/LAMPIRAN.pdf; http://repository.upnvj.ac.id/6535/22/ARTIKEL%20KI.pdf
• Keywords: T Technology (General)

The development of the microblog site is currently very rapid, from what was previously only a means of sharing words between users, now it has become a necessity in the field of business as a means of advertising. One of them is a restaurant, now almost all restaurants use social media as a marketing tool and also to communicate with customers. So that customers are also free to write a comment that is intended as criticism or suggestions for the restaurant or commonly referred to as a review or review. In this application the tweet is classified into two classes, namely negative and positive. This study uses the Support Vector Machine algorithm for the tweet classification process. Data is obtained using the API (Application Programming Interface) provided by Twitter. So that it gets 414 tweets as training data. By using the Support Vector Machine algorithm the test results are obtained with an accuracy of 82,92% with a precision value of 82,92% and a recall value 83%. So it shows the Support Vector Machine algorithm can be used to classify positive and negative sentiments for restaurant reviews.