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All Journal Jurnal Online Mahasiswa (JOM) Bidang Ilmu Hukum Jurnal Komunikasi Hukum Indonesian Journal of Education, Social Sciences and Research (IJESSR) Jurnal Riset Perkebunan (JRP) Buletin Kesehatan: Publikasi Ilmiah Bidang Kesehatan Insight Power (Kekuatan Wawasan) - Jurnal Pengabdian Kepada Masyarakat Digital (JUPED) Menawan : Jurnal Riset dan Publikasi Ilmu Ekonomi JURNAL RUMPUN MANAJEMEN DAN EKONOMI International Journal of Law and Society Al'Adzkiya International of Computer Science and Information Technology Journal
Dimas Prayoga
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Agriculture, Biological Sciences & Forestry Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Nursing Social Sciences Other

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Design of Sentiment Analysis on Indodax Instagram Social Media Comments About Cryptocurrency Using Naïve Bayes Classifier Dimas Prayoga
Al'adzkiya International of Computer Science and Information Technology (AIoCSIT) Journal Vol 5, No 2 (2024)
Publisher : Al'Adzkiya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55311/aiocsit.v5i2.325

Abstract

In today's digital era, social media such as Instagram has become the main platform for many individuals to interact and express opinions online. One application that is often the subject of conversation is Indodax, a well-known digital asset trading platform in Indonesia. This research aims to evaluate the sentiment of Instagram users towards Indodax services through a sentiment analysis approach using Naive Bayes Classifier. The data collected consists of Instagram users' comments, which are analyzed to assess the tendency of their sentiments, whether positive or negative towards Indodax services. This method applies probability and statistical concepts to classify sentiments based on the words present in the comments. It is hoped that the results of this study can provide insights for Indodax to improve the quality of their services based on the perceptions of users. Based on the experiments conducted, the Naive Bayes Classifier method shows fairly accurate classification results, so it can support sentiment analysis related to the Indodax application.
Co-Authors Alif Finno Fidzaky Anisa Enjelina Ariel Adolfo Kesaulya Ayu Sekar Ayunda Febri Kinanti Daniel Jeffry Rivaldo Dedek Kurniawan Dewata Napulangit Dicky Hernando Setiawan Dimas Prakoswo Widiyani Dina Aulia Erdianto Effendi Fitri Herliza Gabriel Batistuta Gabriel Elia Sahala Pandiangan George Mikhael Marsall Hertuida clara Ismi Syafika Jaga Taka Pedro Gonzales Josua Sihombing Juan Rios Ekaharap Laili Hasibuan Linda Kumala Lisvita Melati MHD AZHALI Siregar Muhammad Syahrul Maulana Muhammad Tahir Muhammad Yasin Mutia Evi Kristhy Nur Azizah Paska Puty Andini Rahma Widyana Putri Ramadhani, Fanny Ravindra Singh Safuridar Sri Nurmayanti Widia Edorita