<![CDATA[This study aims to support the computational identification of Quranic themes through a graph theory–based approach. As a case study, the analysis focuses on verses discussing the virtues of the Quran within the framework of graph algorithm applications. The verses are modeled as a graph using an adjacency matrix to represent semantic connectivity between them. The thematic structuring process is conducted by constructing a Minimum Spanning Tree (MST) using the Kruskal Algorithm to obtain an optimal connectivity structure among vertices, followed by the application of Degree Centrality to identify structurally influential vertices corresponding to Quranic verses. The results demonstrate that the combined application of MST and Degree Centrality effectively visualizes the thematic structure of the verses and highlights verses with dominant structural roles in the context of Quranic virtues. Furthermore, the Louvain Algorithm is applied to detect thematic communities, revealing natural clustering patterns that contribute to a more systematic and interpretable thematic mapping. These findings contribute to the advancement of computational Quranic studies by reinforcing data-driven thematic analysis and structured graph-based representations.]]>
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