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Semantic Evolution of the Word Nafs in the Qur'an Based on Contextual Semantics and the Qur'anic Worldview Zakaria, Muhammad Yusuf; Nugroho, Kharis
Proceeding ISETH (International Summit on Science, Technology, and Humanity) 2024: Proceeding ISETH (International Summit on Science, Technology, and Humanity)
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/iseth.5470

Abstract

This study aims to analyze the meaning of the term nafs in the Qur'an using a contextual semantic, syntagmatic, and paradigmatic approach, while also connecting it to the Qur'anic worldview. The research focuses on uncovering the semantic complexity of nafs in three main domains: self-identity, psychological aspects, and spiritual dimensions. A qualitative research method is applied, utilizing primary data from Qur'anic verses containing the term nafs and secondary data from classical exegetical literature, such as Mufradat Alfadh al-Qur'an and Lisan al-Arab. The data is analyzed through syntagmatic analysis to understand the relationship of nafs within the structure of verses and paradigmatic analysis to compare it with other terms such as ruh and qalb. The results reveal that the term nafs exhibits a diverse distribution of meanings in the Qur'an, covering three primary themes: self-identity (112 verses), psychological aspects (98 verses), and spiritual dimensions (85 verses). Syntagmatic and paradigmatic relations enhance contextual understanding, while the analysis of the Qur'anic worldview highlights the central role of nafs in theological, anthropological, and eschatological domains. This study makes a significant contribution to Qur'anic semantics, modern exegesis, and the translation of religious texts. In conclusion, this research integrates classical and contemporary approaches to enrich the understanding of the meaning of nafs in the Qur'an. Further studies are recommended to expand the exploration of this term in other Islamic textual corpora and employ natural language processing technologies for advanced analyses.