Journal of Humanities Research Sustainability

Digital Philology and Manuscript Sustainability: A Semantic Annotation Model for Classical Arabic Texts

Surip Stanislaus — 2025-07-21

Background. The sustainability of classical Arabic manuscripts is often confined to digitization efforts that focus solely on image preservation and limited text markup. These approaches do not fully address the semantic richness and epistemological structure inherent in Islamic intellectual heritage.

Purpose. This study aims to develop a semantic annotation model tailored for classical Arabic texts to support digital philology and enrich manuscript sustainability through machine-readable and concept-linked interpretations.

Method. Using a developmental qualitative research design, three classical manuscripts were annotated semantically using a custom-built model based on RDF and Islamic ontology. The model was evaluated by domain experts in philology and computational linguistics, focusing on four criteria: semantic accuracy, contextual relevance, interoperability, and usability.

Results. The model achieved annotation accuracy above 91% across all manuscripts. Experts rated semantic precision (4.7/5) and contextual relevance (4.6/5) as its strongest aspects. The system successfully mapped technical terms and logical concepts within classical texts and linked them across manuscripts. A case study demonstrated the model’s effectiveness in identifying relationships between epistemological terms and enabling thematic exploration.

Conclusion. This semantic annotation model advances digital philology by enabling structured, concept-based analysis of classical Arabic texts. It bridges computational methods with Islamic textual traditions and opens new pathways for collaborative, sustainable, and meaningful engagement with manuscript heritage.

Pattern Leadership Khulafaur Rasyidin: Analysis History and Valuesfor Modern Life

Muhammad Amiruddin — 2025-07-06

Background. After the death of Prophet Muhammad SAW, Islamic civilization underwent a significant transitional phase under the leadership of the Khulafaur Rasyidin: Abu Bakar Ash-Shiddiq, Umar bin Khattab, Uthman ibn Affan, and Ali ibn Abi Talib. These leaders applied the noble values and teachings of Islam to ensure social stability and to expand Islamic civilization across various regions of the world. Their era marked a critical period of consolidation and ethical governance in the Islamic world.

Purpose. The main purpose of this study is to explore the implementation of key leadership values during the Khulafaur Rasyidin period. These include justice, consultation (shura), responsibility, humility, and leading by example, all of which were essential in shaping a stable and morally grounded Islamic society.

Method. This research uses a literature review method by collecting data from classical Islamic historical texts and relevant scholarly literature. The analysis focuses on identifying leadership traits and values demonstrated during the early caliphate period.

Results. The study reveals that the leadership principles upheld by the Khulafaur Rasyidin significantly contributed to social cohesion, justice, and the overall welfare of the Muslim community during their reign. These values have shown continued relevance and adaptability to modern contexts of ethical leadership.

Conclusion. The legacy of Khulafaur Rasyidin's leadership offers valuable insights for contemporary leaders. By adopting their values, today’s leaders can strengthen their connection with the people, prioritize justice, and uphold social responsibility in governance.

Weaving Imagination: Integrating Artificial Intelligence Into Art Learning to Enhance Student Creativity

Tri Wahyu Martiningsih — 2025-07-21

Background. The integration of artificial intelligence (AI) into education presents transformative opportunities, particularly in the domain of art learning, where creativity is both the process and the product. This study is grounded in the increasing need to reimagine art education by leveraging digital technologies to stimulate and scaffold student imagination and creative expression.

Purpose. The research aims to explore how AI-based tools can be effectively utilized within the art learning environment to enhance students’ creative thinking and artistic innovation.

Method. Employing a qualitative case study approach, data were collected through classroom observations, student artwork analysis, and in-depth interviews with teachers and students from a secondary school implementing AI-assisted art activities.

Results. The findings reveal that the use of AI—especially generative models—positively influences students' ideation processes, broadens their aesthetic perspectives, and fosters a sense of co-creation between human and machine. Furthermore, the study highlights the pedagogical strategies that optimize AI integration, including guided experimentation, reflective discussion, and iterative design.

Conclusion. The research concludes that AI, when meaningfully embedded into art instruction, acts not as a replacement for human creativity but as a catalyst that amplifies students’ imaginative capacities.

Exploration of Syntactic Structure in Virtual Sign Language: A Study on AI-Based Social Media Platforms

Ratna Susanti — 2025-07-06

Background. The virtualization of sign language through artificial intelligence in social media platforms presents linguistic challenges that have not been widely explored, especially related to the accuracy of syntactic structures in digital contexts. These visual representations have the potential to reproduce grammatical misconceptions that impact the meaning and effectiveness of communication.

Purpose. This study aims to explore how the syntactic structure of sign language is represented in a virtual format by AI systems used in social media such as TikTok, Instagram, and YouTube, as well as identify their accuracy and distortions.

Method. The research uses an exploratory qualitative approach with a cross-platform case study design. Data were obtained from 30 virtual sign language videos and analyzed using visual-spatial linguistic frameworks and open coding techniques. Validation is carried out through thematic triangulation analysis and expert consultation.

Results. The results show that the representation of syntactic structure varies greatly between platforms, with YouTube being superior in accuracy to TikTok. Factors such as the length of the video, the sophistication of the algorithm, and the presence of non-manual elements greatly affect the completeness of sentence structure in virtual sign language.

Conclusion. The current representation of sign language by AI does not fully reflect the complex syntactic structure. A new approach is needed in the development of multimodal-based technologies that consider linguistic elements as a whole to make digital communication more inclusive and accurate.