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All Journal Jurnal Pseudocode Sinergi Journal of Information Technology and Computer Science Jurnal SOLMA JCES (Journal of Character Education Society) JOISIE (Journal Of Information Systems And Informatics Engineering) Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) Abdi Reksa
Febriandirza, Arafat
Universitas Muhammadiyah Prof. Dr. Hamka, Indonesia
Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Social Sciences Other

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Journal : Journal of Information Technology and Computer Science

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Sentiment Anlysis On Customer Reviews Using Support Vector Machine and Usability Scoring Using System Usability Scale Novira Azpiranda; Ahmad Afif Supianto; Nanang Yudi Setiawan; Endang Suryawati; R. Sandra Yuwana; Arafat Febriandirza
Journal of Information Technology and Computer Science Vol. 6 No. 3: December 2021
Publisher : Faculty of Computer Science (FILKOM) Brawijaya University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jitecs.202163330

Abstract

Al-Ghiff Steak is a restaurant located in Cirebon City that offers quality steaks at affordable prices. For maintaining a competitive Al-Ghiff Steak advantage and reputation, it is important to build a good relationship with customers and have a business strategy that considers customer opinions. However, in its implementation, Al-Ghiff Steak has difficulty when collecting and processing customer review data manually. Therefore, it is necessary to conduct sentiment analysis by utilizing Google Reviews to determine customer perspectives regarding Al-Ghiff Steak products and services. This analysis was conducted on 968 Google Review reviews from 2016 to 2020 using the Support Vector Machine (SVM) and Term Frequency-Inverse Document Frequency (TF-IDF) methods. Classification testing is done with a confusion matrix against four parameters: accuracy, precision, recall, and f1-score. SVM with TF-IDF gets accuracy value 83%, precision 64%, recall 60% and f1-score 59%. The sentiment classification result is then visualized in the form of a dashboard. We utilize the System Usability Scale (SUS) for usability testing, which produces a value of 77.5. This result achieve the Acceptable category and an Excellent rating.
Co-Authors Abdiel Alpriyan Gempa Alamsyah Sahuri Ade Maya Saraswati Ahmad Afif Supianto E Erizal Eka Kartikawati Endang Suryawati Endy Syaiful Alim Faldy Irwiensyah Firman Noor Hasan Firman Noor Hasan Hibatullah Faisal Irdalisa Irdalisa Maesaroh Maesaroh Mega Elvianasti Muhamad Wahyu Sanjaya Muhammad Hafizd Ibnu Hajar Muhammad Solehuddin Al-Khawarizmi Nanang Yudi Setiawan Novira Azpiranda Prastika Indriyanti Prastika Indriyanti R. Sandra Yuwana Rahady Puji Alfiansyah Rahmi Imanda Suwoyo, Heru Widia Anggraeni