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All Journal Jurnal Informatika Perspektif : Jurnal Ekonomi dan Manajemen Universitas Bina Sarana Informatika Jurnal Teknik Komputer AMIK BSI Paradigma Jurnal Pilar Nusa Mandiri Techno Nusa Mandiri : Journal of Computing and Information Technology JURNAL TEKNOLOGI DAN OPEN SOURCE Jurnal Riset Informatika Journal of Information System, Applied, Management, Accounting and Research Jurnal Informatika Kaputama (JIK) JURSIMA (Jurnal Sistem Informasi dan Manajemen) JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Journal of Computer System and Informatics (JoSYC) JPM: JURNAL PENGABDIAN MASYARAKAT Jurnal Responsif : Riset Sains dan Informatika Bulletin of Computer Science Research Journal of Informatics Management and Information Technology KLIK: Kajian Ilmiah Informatika dan Komputer Computer Science (CO-SCIENCE) Reputasi: Jurnal Rekayasa Perangkat Lunak Jurnal Abdimas Komunikasi dan Bahasa Profitabilitas Indonesian Journal of Networking and Security - IJNS JUSTIN (Jurnal Sistem dan Teknologi Informasi) Jurnal Interkom : Jurnal Publikasi Ilmiah Bidang Teknologi Informasi dan Komunikasi J-Intech (Journal of Information and Technology) DEVICE : JOURNAL OF INFORMATION SYSTEM, COMPUTER SCIENCE AND INFORMATION TECHNOLOGY JEECS (Journal of Electrical Engineering and Computer Sciences) JURSIMA Sinergi: Jurnal Pengabdian Kepada Masyarakat Journal of Accounting Information System Bulletin of Informatics and Data Science Jurnal Sistem Informasi dan Manajemen Journal of Artificial Intelligence and Technology Information Media Teknologi dan Informatika Darma Abdi Karya: Jurnal Pengabdian Kepada Masyarakat Jurnal Informatika dan Rekayasa Perangkat Lunak Jurnal Komtika (Komputasi dan Informatika) Journal of Information Technology Jurnal Teknoinfo
Riska Aryanti
Universitas Bina Sarana Informatika, Indonesia
Aerospace Engineering Agriculture, Biological Sciences & Forestry Humanities Astronomy Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Medicine & Pharmacology Public Health Social Sciences Transportation Other

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Journal : Jurnal Riset Informatika

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Sentiment Analysis of E-Grocery Application Reviews Using Lexicon-Based and Support Vector Machine Aryanti, Riska; Fitriani, Eka; Royadi, Royadi; Ardiansyah, Dian; Saepudin, Atang
Jurnal Riset Informatika Vol. 6 No. 3 (2024): June 2024
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34288/jri.v6i3.301

Abstract

This research aims to conduct sentiment analysis of e-grocery application reviews using the Support Vector Machine (SVM) algorithm. Sentiment analysis is used to distinguish between positive and negative reviews by users who have provided reviews so that an evaluation of the services offered can be made. This research uses scraping techniques to obtain all the needed review data, focusing only on reviews of the Segari and Sayurbox applications. Datasets were collected from reviews using a library in Python, namely, google-play-scraper, obtained by the sayurbox application 4235 reviews and the segari application 5575. The dataset collected does not yet have a label, and the labeling process is impossible to perform manually by looking at the reviews one by one because it takes a long time and requires an expert in the field of language who can interpret the reviews and group them into positive and negative sentiments. Therefore, the sentiment-labeling process applies a lexicon-based method that works based on the inset lexicon dictionary by calculating each review's polarity value. The analysis process of this research uses the SVM algorithm because the SVM method has been proven to provide consistent and accurate results in various classification tasks, including sentiment analysis. The results show that the lexicon-based method and SVM produce good accuracy in determining the sentiment of e-grocery reviews, with a vegetable box application accuracy rate of 94%. In comparison, the segari application accuracy rate reached 97%.
Co-Authors Agus Junaidi Agustiani, Sarifah Aldian Mauluda Alif Rizqi Mulyawan Andi Saryoko Andika Bayu Hasta Yanto Andreas Roy Prasetya Ari Sulistiyawati Ari Sulistiyawati Arifin, Yosep Tajul Asriyani Sagiyanto ASRIYANI SAGIYANTO, ASRIYANI Atang Saepudin Atang Saepudin Atang Saepudin Azis, Munawar Abdul Bayu Kusuma Ilyasa Universitas Bina Sarana Informatika Dahlia Dahlia Darma Setiawan Putra Dede Firmansyah Dede Firmansyah Saefudin Dedi Darwis Deni Gunawan Diah Puspitasari Dian Ardiansyah Dian Ardiansyah Dyah Ayu Megawaty Eka Dyah Setyaningsih Eka Fitriani Eka Fitriani Eka Fitriani Eka Fitriyani Fachri, Muhamad Faruk Ulum Haliza Ramadhanti, Pristya Harefa, Kristine Haryani Hasan, Fuad Nur Henny Leidiyana Herdian Pratama I Gede Iwan Sudipa Irfan Ridwan Jananto Watori Junhai Wang Kamil, Anton Abdul Basah KOMALASARI, YULI Martenia, Rina Masngud Megawaty, Dyah Ayu Mesran, Mesran Mochamad Wahyudi Oktaviyani Oktaviyani Oprasto, Raditya Rimbawan Pasaribu, A. Ferico Octaviansyah Perani Rosyani Pristya Haliza Ramadhanti Rachilsyah Ramdhani Efendi Rahmat Hidayat Rahmat Hidayat Ramadhani, Arman Ramadhani, Arya Richardus Eko Indrajit Rifky Permana Rifqi Rizaldi Rina Martenia Rizqi Nur Esmeralda Rosiun Universitas Bina Sarana Informatika Roy Prasetya, Andreas Royadi Royadi - Royadi Royadi Royadi, Royadi Salman Alfarizi SALMAN ALFARIZI Samudi Sari Dewi Universitas Bina Sarana Informatika PSDKU Pontianak Setiawansyah Setiawansyah Siti Khotimatul Wildah Siti Marlina, Siti Sopiyan Dalis Sumanto Sumanto Titik Misriati tri wahyuni Tri Wahyuni Ulum, Faruk Wahyudi, Agung Deni Walim Walim Wang, Junhai Yarimani Laia