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The Qur'an al-Karīm employs at least four principal terms in referring to human beings, namely al-basyar, al-insān, al-nās, and banī Ādam. These terms are not merely synonymous; rather, each represents distinct yet complementary dimensions of humanity in constructing a holistic concept of the human being. This study aims to: (1) analyze the semantic meanings of these four terms based on mufrodat studies, Makkiyah-Madaniyah classification, and asbābun nuzūl; (2) compare the interpretations of classical scholars - Al-Ṭabarī, Ibn Kathīr, Al-Qurṭubī, and Fakhr Al-Rāzī - with those of contemporary scholars - Sayyid Quṭb, Ibn ‘Āshūr, M. Quraish Shihab, and Buya Hamka; and (3) formulate their implications for Islamic education. This research employs a library research method using the tafsīr maudhū‘ī approach integrated with Izutsu’s semantic analysis model. The findings reveal that al-basyar represents the physical-biological dimension of human beings; al-insān represents the spiritual dimension in relation to ‘ubūdiyyah toward Allah; al-nās represents the social-collective dimension; and banī Ādam represents the intellectual-rational dimension inherited from Adam through the divine gift of teaching al-asmā’ (Qur'an 2:31). Collectively, these four dimensions provide fundamental implications for the development of objectives, curriculum, methodology, and evaluation within holistic and comprehensive Islamic education.

This research is driven by the significance of examining language meaning, particularly connotative meaning which is often used to convey implicit messages in literary works. Folktales, as one type of oral literature, often utilize character names that carry specific meanings, such as Malin Kundang from Minangkabau. The aim of this research is to uncover the connotative meaning of the character name “Malin Kundang”, as well as its relationship with the moral and cultural values of the society. The methodology involves qualitative research using semantic analysis and a descriptive approach. Data were collected from the Malin Kundang folktale text thru library study and documentation techniques. Next, the processes of identification, classification, and interpretation of meaning were done in order to examine the data. The research result show that denotatively, the name Malin Kundang only functions as the identity of the character, but connotatively, it functions as a symbol of a disobedient child who does not respect their parents. The meaning is formed from the plot of the story and reinforced by the Minangkabau cultural values that uphold respect for parents. The implications of this research indicate that the naming of characters in folklore is not only linguistic but also reflects the moral and cultural values inherited by society.

Prompt injection has emerged as a critical security threat for Large Language Models (LLMs), exploiting their inability to separate instructions from data within application contexts reliably. This paper provides a structured review of current attack vectors, including direct and indirect prompt injection, and highlights the limitations of existing defenses, with particular attention to the fragility of Known-Answer Detection (KAD) against adaptive attacks such as DataFlip. To address these gaps, we propose a novel, hybrid, multi-layered detection framework that operates in real-time. The architecture integrates heuristic pre-filtering for rapid elimination of obvious threats, semantic analysis using fine-tuned transformer embeddings for detecting obfuscated prompts, and behavioral pattern recognition to capture subtle manipulations that evade earlier layers. Our hybrid model achieved an accuracy of 0.974, precision of 1.000, recall of 0.950, and an F1 score of 0.974, indicating strong and balanced detection performance. Unlike prior siloed defenses, the framework proposes coverage across input, semantic, and behavioral dimensions. This layered approach offers a resilient and practical defense, advancing the state of security for LLM-integrated applications.