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All Journal JURNAL MATEMATIKA STATISTIKA DAN KOMPUTASI Elkom: Jurnal Elektronika dan Komputer JURNAL PENGABDIAN KEPADA MASYARAKAT Jurnal Cendekia : Jurnal Pendidikan Matematika Jurnal Nasional Komputasi dan Teknologi Informasi Jurnal Abdidas Djtechno: Jurnal Teknologi Informasi INCODING: Journal of Informatics and Computer Science Engineering Teknik: Jurnal Teknik Mesin, Elektro dan Ilmu Komputer
Arnita Arnita
Universitas Negeri Medan
Aerospace Engineering Arts Humanities Automotive Engineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Health Professions Languange, Linguistic, Communication & Media Mathematics Neuroscience Public Health Social Sciences Transportation Other

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Analisis Sentimen Ulasan Pada Aplikasi E-Commerce Shopee Dengan Menggunakan Algoritma Naïve Bayes Rahel Lina Simanjuntak; Theresia Romauli Siagian; Vina Anggriani; Arnita Arnita
Jurnal Teknik Mesin, Elektro dan Ilmu Komputer Vol. 3 No. 3 (2023): November : Jurnal Teknik Mesin, Elektro dan Ilmu Komputer
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/teknik.v3i3.2411

Abstract

Every year, the e-commerce industry in Indonesia grows and develops at a rapid pace. In Indonesia, many online marketplaces have sprung up, including Tokopedia, Lazada, and Shopee. People are very interested in all e-commerce companies because they are hassle-free and instant. Among the most famous is Shopee, which offers a wide range of services and also presents a ratings and reviews column. This feature allows users to express their feelings about Shopee. Based on the information gathered from previous user comments, consumers can use these ratings to identify and trust both excellent and negative recommendations of the app they want to use. Sentiment analysis results include both favorable and negative user reviews by scoring, classifying, and filtering viewpoints to help businesses or users. The author uses the naïve bayes algorithm in this research. The Naïve Bayes Classifier approach will be used in this research to perform sentiment classification. The author then uses associations between frequently discussed word terms or themes that are related to each other for the extraction and exploration process, as well as descriptive statistics. Naïve Bayes Classifier is a binary classification technique that applies Bayesian principles with a strong assumption of independence, utilizing simple statistical probabilities.
Co-Authors Angelita Anggi Sean Manuella Limbong Diah Retno Wahyuningrum Dian Septiana DIdi Febrian Evelyn Keisha Silalahi Fahrur Rozi Hermawan Syahputra Insan Taufik Isda Pramuniati Iwan Agi Berutu Khildan Rifail Azis M. Revano Ananda Lubis Marpaung, Faridawaty Muhammad Naufal Musyafa Rahel Lina Simanjuntak Ramadhani, Fanny Raudah Ummu Fahda Damanik Rosmaini Sahat Saragih Said . Iskandar Sinaga, Marlina Setia Theresia Romauli Siagian Vina Anggriani Yulita Molliq