Rafil Moehamad Alif

Implementation of the BiLSTM Model for Detecting AI-Generated Indonesian Text

This study develops a text detection system specifically for the Indonesian language using a Deep Learning approach with a Bidirectional Long Short-Term Memory (Bi-LSTM) architecture that achieved a 93.77% success rate in identifying human-written texts, though it logged a lower detection rate for academic AI text structures.