Zaytuna College

This study holds particular significance for small and medium-sized enterprises, where limited resources often necessitate the efficient conversion of strategic capabilities into measurable performance outcomes. The proposed conceptual model aims to elucidate the intricate relationships among these variables, providing a comprehensive understanding of the mechanisms that underpin organizational performance in resource-constrained settings. The objective of this research is to explore the direct effects of dynamic capability and entrepreneurial orientation on innovation capability and organizational performance, as well as the mediating role of innovation capability in these relationships. The study employs a cross-sectional survey method, collecting data from 396 SMEs in Bali, Indonesia, using an online questionnaire. The data were analyzed using variance-based structural equation modeling. Results from the analysis reveal that dynamic capability has a strong positive effect on both innovation capability and organizational performance. Entrepreneurial orientation significantly impacts innovation capability, but its direct effect on organizational performance is negligible. However, innovation capability fully mediates the relationship between entrepreneurial orientation and organizational performance. The study also found that mediation analysis of innovation capability on dynamic capability to organizational performance suggest that there is almost no mediating effect.

Helicobacter pylori (H. pylori) infection remains a major health problem in developing countries because of its high prevalence. H. pylori colonizes the stomach of children and causes local inflammation. Accurate diagnosis is essential to ensure appropriate treatment and reduce the risk of long-term complications. In Libya, limited data are available regarding H. pylori diagnostic methods. The Objective of this study was to compare the diagnostic performance of invasive and non-invasive methods for detecting H. pylori infection among pediatric dyspeptic patients (histopathology method and serology method). A gastric biopsy and a blood sample were collected from 120 dyspeptic children attending the gastroenterology units at Tripoli Children's Hospital. The overall prevalence of H. pylori infection was 84% using the invasive method, and 51% using the non-invasive method. The histopathology-based diagnostic method is the gold standard diagnostic tool for H. pylori detection. However, additional research with a higher number of patients and in other areas of Libya should be conducted in the future to confirm the study's findings.

Pavement performance assessment and prediction are crucial for efficient infrastructure management and strategic planning of maintenance activities. Conventional techniques are insufficient and lack the efficiency and flexibility required for modern transportation networks. This study proposes a groundbreaking integrated approach that merges machine learning (ML) classification techniques with Geographical Information Systems (GIS) to evaluate road conditions using the Pavement Condition Index (PCI) and the International Roughness Index (IRI). Given that IRI data collection is more straightforward and cost-effective than gathering pavement distress data, this study aims to classify the IRI of flexible pavements to estimate PCI models using advanced ML algorithms (Artificial Neural Network (ANN), Adaptive Boosting (AdaBoost), Support Vector Machine (SVM), Decision Trees (DT), and Random Forest (RF)) and accurately determine pavement conditions. This research gathered 1042 data points using a smartphone application, TotalPave, to measure the IRI values for the (Nizwa–Muscat) and (Muscat–Nizwa) routes in the Sultanate of Oman. It meticulously applied feature selection techniques to identify the pavement parameters significantly impacting pavement performance. The research then spatially visualized and analyzed the results to determine the critical pavement sections. Among the ML models, RF demonstrated outstanding performance with an accuracy rate of 99.9% and an F1-score of 99. SVM has the lowest accuracy of 85.8% and an F1-score of 40.3. A comprehensive assessment comprising a confusion matrix, uncertainty analysis, box and whisker plot, and noise sensitivity provides in-depth insights into the reliability and consistency of predictions. The ML and GIS methods revolutionized the way transportation agencies interpret and implement their findings. The proposed framework is not merely a tool, but a transformative solution that facilitates the formulation of proactive maintenance strategies and optimizes resource utilization by providing a scalable and intelligent decision-support tool designed specifically for pavement management systems (PMS).

The study highlighted that ADO.NET offers a practical and reliable solution for the Libyan labor market, particularly for organizations dealing with unstable internet, large datasets, or the need to strengthen practical skills among local developers. Its hybrid architecture allows data to be processed locally before synchronization, reducing reliance on constant connectivity and improving the performance of large and complex applications. The disconnected connection model makes it especially useful in environments with limited or inconsistent network access. Survey results showed that most students found ADO.NET easier to learn and more efficient compared to traditional ADO and ORM, and they preferred using it in their own projects. Based on these findings, the study recommends adopting ADO.NET for projects that demand high control and efficiency, integrating it into academic curricula, and providing hands-on training to ensure developers and students can use it effectively. Organizations are also encouraged to implement best practices for managing connectivity challenges and to continuously update skills and assess the technology to maximize its benefits and maintain high levels of operational effectiveness.

This research addresses the issue of the administration's refusal to implement judicial rulings, highlighting the reasons that lead to this refusal and its effects on the principle of the rule of law and individual rights. The research reviews legal experiences and shows the challenges facing the implementation of rulings, including bureaucracy, lack of resources, and political pressures. The research also provides guidelines to enhance the effectiveness of the legal system, including improving legislation, establishing specialized executive units, and strengthening oversight and accountability. The research aims to emphasize the importance of implementing rulings as a fundamental factor in achieving justice and protecting human rights.

This study aims to examine grammatical errors in opinion essays written by Post-Intermediate Level students at the Bali International Language Centre (BILCEN) at Triatma Mulya University, utilising DeepSeek AI to discover error trends and offer strategic advice for educators. A qualitative analysis of 17 articles revealed 109 grammatical problems, predominantly characterised by article omission errors (42.2%), followed by subject-verb agreement (26.6%), preposition errors (17.4%), and tense inconsistencies (13.8%). The primary reasons for these errors encompass first-language interference and sentence fragmentation, indicative of the impact of Indonesian structures on English production. Examples include “work in a cruise ship” rather than “work on a cruise ship.” This study underscores the significance of a teaching methodology incorporating contrastive exercises, targeted feedback, and task design that balances fluency and accuracy. Strategic recommendations involve implementing exercises that juxtapose Indonesian and English structures and utilizing DeepSeek AI’s functionalities to provide comprehensive feedback. This study presents a novel approach for educators to tackle systematic grammatical issues in EFL students’ opinion writing. It underscores the potential of AI to enhance the precision of academic writing.

Abstract This essay reflects on the challenges and opportunities of constructing a Muslim theology within academic frameworks. It uses Andrew Louth's essay Theology and Spirituality as a lens to think about the different dimensions of theological inquiry and what that means for the study of Islamic theology in the academy. Louth emphasizes that theology must integrate intellectual inquiry with an embodied relationship to truth. This essay applies this framework to Islamic theology, exploring its treatment in academia through three primary approaches: historical‐philological studies, propositional truth grounded in rational discourse, and authentic responses to revelation. While these methods contribute to understanding theology, they often neglect experiential and spiritual dimensions. Drawing on Louth and insights from Islamic tradition, this essay highlights the construction of Islamic theology by the secular academy in its focus on intellectual history and propositional modes of inquiry, contrasted with the embodied practices essential for a theology rooted in divine intimacy.