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All Journal Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer
Salsabila Rahma Yustihan
Fakultas Ilmu Komputer, Universitas Brawijaya
Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering

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Analisis Sentimen berbasis Aspek terhadap Data Ulasan Rumah Makan menggunakan Metode Support Vector Machine (SVM) Salsabila Rahma Yustihan; Putra Pandu Adikara; Indriati Indriati
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 5 No 3 (2021): Maret 2021
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Internet is a huge virtual space for people to share everything to others effectively including reviews. Reviews provided by someone on the internet have a big impact on other users and company. One of the most frequent reviews in internet is restaurant reviews. One restaurant review can contain several different aspects, to find out the aspects and sentiments contained in a review, an aspect-based sentiment analysis is needed. The data used in this study is restaurant review data obtained from SemEval-2016 Task 5 with 300 training data and 100 test data. To find out what aspects are contained in a review, opinion extraction is needed by doing POS tagging and extract the document into several opinions according to the basic grammar, then to classifying aspect and sentiment contained in a review, Support Vector Machine with the One-Against-All strategy is used in this research. The results of the evaluation using confusion matrix on aspect classification and sentiment classification produce precision of 0,94 and 0,86, recall of 0,6 and 0,98, accuracy of 0,88 and 0,86, and f-measure of 0,73 and 0,92.
Co-Authors Indriati Indriati Putra Pandu Adikara