Hallucinating the archipelago: detecting factual and cultural errors in retrieval-augmented generation for Indonesian knowledge - Radna Tulus Wibisono (CV Narasi Khatulistiwa Indonesia, 2026)
Background: Retrieval-augmented generation has been promoted as a practical response to hallucination in large language models, yet Indonesian knowledge presents a harder evidential problem because factual claims are often inseparable from regional attribution, cultural terminology, legal classification, and administrative scope. Objective: This study examines how factual and cultural errors appear in RAG-generated answers about Indonesian knowledge and how such errors can be traced across claim alignment, retrieval provenance, and cultural specificity. Method: Using a qualitative-computational design, this study evaluates 186 claim units derived from a public-source corpus of Indonesian cultural-heritage records, legal documents, statistical portals, lexical references, government explainers, and local institutional sources. Results: The findings indicate that RAG performs most reliably when generated claims reproduce explicit institutional facts, such as official entities, legal instruments, statistical categories, and cultural-heritage designations. However, unsupported and partially supported claims emerge when retrieved evidence is general, incomplete, or transformed into causal, nationalising, or culturally overextended explanations. Implication: Cultural errors are especially visible in regional scope reduction, terminological loss, ritual simplification, and temporal or administrative decontextualisation. Novelty: The novelty of this study lies in integrating claim–evidence alignment, retrieval-provenance diagnosis, and cultural-specificity coding into one framework for evaluating Indonesian RAG hallucination