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Indonesia is in an earthquake-prone region, therefore, designing building constructions that can withstand seismic loads is crucial in civil engineering. Reinforced concrete shear walls are one of the vertical structural fundamentals that are effectively used in multi-story buildings to withstand lateral forces due to earthquake and wind loads. Structures that use shear walls can increase stiffness and reduce horizontal deviations (deflections) of buildings, which contribute to the stability and safety of structures based on the SNI 1726:2019 standard. This study aims to analyze the effect of shear wall configurations on deviation and torsion requirements in multi-story building planning. The study object is a 6-story reinforced concrete building model in a specific earthquake zone. The design and modeling were performed using structural analysis software, taking into account columns, beams, slabs, and shear walls. The analysis results show that optimal placement of shear walls at the building edges significantly reduces horizontal drift, torsion, and shear forces, and improves the structural performance level compared to structures without shear walls or those with less effective placement. Structures with shear walls have optimal stiffness in absorbing lateral forces, making them more resistant to damage from the planned earthquake.

The use of moldboard plows in agricultural land preparation often faces wear problems on the share component, leading to increased maintenance time and reduced operational efficiency. This study aims to design and analyze a modular concept for the plow share to improve maintenance and repair efficiency without compromising structural performance. The research methods include field observation, component dimension measurement, design modeling using CAD software, and structural analysis using the Finite Element Analysis  (FEA) method. In addition, maintenance ease was evaluated through a questionnaire based on a rating scale. The results show that the modular design significantly improves maintenance and repair efficiency, with an average score of 4.59 categorized as very good. Structural analysis indicates that the modular design reduces maximum stress on the moldboard and slightly decreases deformation, reflecting improved structural stiffness compared to the conventional design. However, the Safety Factor on the share component remains below the acceptable limit, indicating the need for further development. Overall, the modular design provides an effective solution to enhance maintenance efficiency while maintaining the structural performance of the moldboard plow.

Explainable artificial intelligence (XAI) has become a critical requirement in cybersecurity due to the high-stakes nature of security decision-making and the limitations of black-box learning models. This study investigates the construction of an explainable cybersecurity knowledge representation by leveraging standardized terminology from the NIST cybersecurity glossary. The primary problem addressed is the lack of transparent and semantically grounded reasoning mechanisms in existing AI-driven cybersecurity systems, which limits trust, accountability, and analyst adoption. To address this challenge, we propose a NIST-based semantic knowledge graph that embeds explainability directly into its ontology structure and reasoning process. The proposed framework systematically extracts definitional entities and relations from NIST glossary entries to construct a domain ontology and a multi-relational knowledge graph. A rule-based semantic relation extraction method is employed to ensure faithful, interpretable, and reproducible reasoning paths. The resulting knowledge graph contains over 3,000 cybersecurity concepts and approximately 27,000 semantic relations, covering hierarchical, associative, dependency, and mitigation semantics. Experimental evaluation demonstrates that the proposed approach achieves a high level of explainability, with 92.4% of reasoning outcomes being fully traceable and only 1.4% classified as non-traceable. Most explainable reasoning paths are limited to two or three hops, indicating an effective balance between inferential depth and human interpretability. Structural analysis further confirms the presence of meaningful hub concepts that support multi-hop semantic inference. These results confirm that ontology-driven, standard-based knowledge graphs provide a robust foundation for explainable cybersecurity intelligence. The study concludes that explainability-by-design, grounded in authoritative standards, offers a viable and trustworthy alternative to opaque AI models for cybersecurity applications.

This study investigates the role of Enterprise Information Systems (EIS) in driving innovation within organizations. The research employs a mixed-method approach, combining survey-based structural analysis and in-depth organizational case studies to explore how different EIS capabilities influence organizational innovation. The study focuses on four key EIS capabilities: functional capabilities such as workforce management and customer value creation; technological capabilities including ERP systems and real-time analytics; dynamic capabilities, especially organizational learning; and collaborative innovation through external partnerships. The survey results reveal that EIS capabilities, particularly data analytics and integration, significantly enhance organizational agility, decision-making, and innovation outcomes. In-depth case studies provide detailed insights into how these capabilities are applied in real-world organizational settings, illustrating their impact on process and service innovation. The findings indicate that the effective integration of EIS across organizational functions, along with improved access to data, contributes to operational efficiency and innovation success. However, challenges such as integration issues, resistance to change, and lack of skilled personnel were also identified as barriers to successful EIS adoption. The study contributes to the literature by offering a comprehensive understanding of how EIS capabilities drive innovation and highlighting the importance of organizational culture and leadership in the adoption process. The research provides practical recommendations for organizations to leverage EIS for fostering innovation, such as focusing on EIS integration, overcoming organizational barriers, and ensuring leadership engagement. Finally, the study suggests future research directions, including the refinement of multi-method approaches and the need for longitudinal studies to better understand the long-term impact of EIS on innovation outcomes.

This study examines the short story "Click that Kills" by Taufiqurohman to reveal the position of humans in the increasingly dominating digital algorithm environment. Using a descriptive qualitative approach that focuses on structural analysis and literary psychology based on Freud's psychoanalytic theory, this study thoroughly analyzes the intrinsic elements as well as the inner conflicts of the characters. The findings of this study show that the AIDA system poses a profound existential crisis, where individual freedom is threatened due to systemic information manipulation. The characters of Dito and Genta experience a serious conflict between id, ego, and superego when dealing with the figure of "Shadow User" who is a real symbol of the shift in human dignity through raw data. In terms of structure, the storyline conveys a deep social critique of the loss of human self-control in cyberspace. This research shows that this short story is a premonious criticism of the importance of maintaining the essence of humanity in the midst of the prevalence of mechanical algorithms. The phenomenon emphasizes that digital technology can potentially alienate the moral consciousness of individuals in modern society.

This study analyzes a 10-floor multi-story lecture building in Lombok, focusing on the impact of concrete quality degradation on the building's performance. Due to limited material access, the actual on-site concrete quality changed from the design quality of fc 30 MPa to fc 24.9 MPa. The building structure was modeled in 3D using ETABS v22 software, and two structural models were compared: one with the design concrete quality (fc' 30 MPa) and one with the actual quality (fc' 24.9 MPa). The analysis evaluated dynamic performance, inelastic displacements, P-Delta effects, and reinforcement requirements. The comparison aimed to assess the impact of concrete degradation on structural stiffness, inter-story displacements, and reinforcement needs. The results show that concrete quality deterioration increases the structure's vibration period, inelastic displacement, and lateral forces due to P-Delta effects. While beam reinforcement requirements remain mostly unchanged, column reinforcement significantly increases, especially in columns with large axial forces. This study provides valuable insights into the technical consequences of concrete quality degradation and serves as a reference for evaluating structural redesigns in projects facing material limitations.