EVALUATION OF THE QUALITY OF LARGE LANGUAGE MODELS' ANSWERS IN ANSWERING RELIGIOUS QUESTIONS FOR DIGITAL DA'WAH - Munirah Munirah; Aslan Alwi; Abdul Karim (STAI Asy-Syukriyyah, 2026)
The development of Large Language Models (LLMs) has opened new opportunities for utilizing artificial intelligence for digital da'wah. However, the use of LLMs in the religious domain presents challenges related to accuracy, potential errors (hallucinations), and conformity with Islamic values. This study aims to evaluate the quality of LLM responses in answering religious questions as part of digital da'wah. The method used is a descriptive evaluation of 125 religious questions covering aspects of worship, faith, morals, contemporary issues, and ambiguous questions. LLM responses were analyzed based on three main indicators: accuracy, potential hallucinations, and conformity with Islamic values. The results show that LLMs have a fairly good level of accuracy on basic religious questions, but the potential for hallucinations is still found, especially in ambiguous and contemporary questions. These findings indicate that LLMs have potential as a digital da'wah tool, but their use requires a verification mechanism to maintain accuracy and conformity of values.