Detection of Indonesian wildlife sales and promotion through social media using machine learning approach

Dinda Lestarini, Taufiqurrahman Rusdy, Silfi Iriyani, Sarifah Putri Raflesia


Social media is one of the communication media that is widely used in the digital era as it is today. The use of social media allows people who are far apart to communicate and exchange media, both voice, video, and images quickly and even in real-time. In the past, the sale of protected animals was mostly done on the black market, usually involving a supply chain between sellers that usually existed in traditional markets or certain communities. With the existence of social media, the trend in conducting transactions and promoting wild animals has shifted from traditional to modern thanks to the support of existing technology. Protected wild animals are of concern to the local government or the global world to protect their existence. Therefore, this research proposes a machine learning (ML) based approach to detect the promotion and sale of wild animals on social media. The implementation of Naïve Bayes classifier (NBC) has a high accuracy in detecting trade in wild animals on social media with an accuracy value of 86. The implementation of ML-based approach is expected to produce new technology that allows authorities to know and monitor social media in order to reduce the sale and promotion of protected wildlife.


Machine learning; Naïve Bayes classifier; Social media; Wildlife trade

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Bulletin of EEI Stats

Bulletin of Electrical Engineering and Informatics (BEEI)
ISSN: 2089-3191, e-ISSN: 2302-9285
This journal is published by the Institute of Advanced Engineering and Science (IAES) in collaboration with Intelektual Pustaka Media Utama (IPMU).