Analysis of Public Sentiment towards the Security of Using B2C E-Commerce Using Naïve Bayes Approach Based on Text Mining to Prevent Fraud
DOI:
https://doi.org/10.33379/gtech.v8i3.4846Keywords:
sentiment analysis, security, e-commerce, naïve bayes, fraudAbstract
The Society 5.0 Era's technology development has shifted marketing communication from face-to-face to screen interaction, like online shopping via e-commerce. According to Statista Market Insight data, e-commerce users in Indonesia reached 178.94 million in 2022, with transactions totaling Rp476.3 trillion. Despite its growth, e-commerce is prone to cybercrime, with 16,845 reports to the National Police's Ditipideksus from 2017 to 2020. This research analyzes public sentiment on e-commerce security through Play Store and App Store comments. The Naïve Bayes model shows an accuracy of 80% on the Play Store and 87% on the App Store, with AUCs of 0.864 and 0.942, respectively, indicating excellent sentiment classification performance. The findings aim to help B2C e-commerce providers enhance security through advanced technologies, user education, fraud detection systems, and improved transparency and response to security incidents, thereby increasing user trust.
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Copyright (c) 2024 Marcelena Vicky Galena, Adnan Syawal Adilaha Sadikin, Aprilia Prastyaningrum, Reza Febrian Nugroho, M. Fariz Fadillah Mardianto
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