Abstract:The digital technology revolution has catalyzed a fundamental paradigmatic transformation in the global education ecosystem, creating a new era where technology integration has become a strategic imperative in effective…
and sustainable learning management. One of the most disruptive technological innovations that has become the primary focus in educational transformation is Artificial Intelligence (AI), which has demonstrated extraordinary potential in revolutionizing various aspects of learning management through sophisticated adaptive capabilities, deep learning personalization, and comprehensive administrative automation. This research aims to comprehensively and systematically examine the multidimensional role of AI in enhancing the quality of learning management in the digital era, with in-depth analytical focus on three fundamental pillars: strategic learning planning, pedagogical process implementation, and learning outcome evaluation. The research methodology employs a rigorous Systematic Literature Review (SLR) approach, analyzing over 150 high-quality scientific articles from leading national and international journals published between 2014-2024, utilizing a thematic synthesis framework to identify emergent patterns and significant trends in AI implementation in education. Research findings reveal that AI implementation in learning management produces multifaceted transformative impacts, including significant improvements in pedagogical decision-making quality through predictive analytics and data-driven insights, strengthening the strategic role of teachers as adaptive and responsive learning facilitators, and expanding democratic learning accessibility through adaptive learning systems and intelligent tutoring systems technologies. AI has also proven effective in optimizing educational resource allocation, enhancing student engagement through intelligent gamification, and facilitating inclusive and equitable learning.
However, this research also identifies complex challenges that must be addressed in AI implementation, including significant technological infrastructure gaps particularly in remote areas, limitations in educators' digital literacy affecting technology adoption, and ethics and data privacy issues requiring comprehensive regulatory frameworks. The implications of this research emphasize the need for a holistic and structured approach in integrating AI into educational systems, considering technological, pedagogical, and socio-cultural aspects in a balanced manner to achieve sustainable and positively impactful educational transformation.
Abstract:This study aims to analyze the evaluation of public policy and environmental disaster mitigation predictions regarding the cancellation of the strategic glass industry development in Rempang Island. The study employed a…
qualitative approach with a case study design and data collection through systematic literature review. Data analysis was conducted using the interactive model of Miles, Huberman & Saldana (2014). The results show that the Rempang Eco City National Strategic Project (NSP) failed comprehensively due to a procedurally flawed and non-participatory formulation process. Economic valuation research by Trend Asia et al. (2025) found that the average household income of Rempang residents reached IDR 32.77 million per household per month, far exceeding the government’s claim of IDR 3 million, while potential environmental losses reached IDR 109 million per household per month. Based on Dunn’s (2003) six policy evaluation criteria, this policy proved to be ineffective, inefficient, inadequate, inequitable, unresponsive, and inappropriate. President Prabowo Subianto’s decision to exclude Rempang Eco City from the NSP list through Presidential Regulation No. 12 of 2025 was the right step, yet still requires more decisive regulation to provide legal certainty for affected communities.
Abstract:Karstification is the dominant geological process controlling groundwater circulation and permeability in carbonate aquifers. Through the dissolution of carbonate rocks, karst processes create highly heterogeneous systems…
s characterized by fractures, conduits, and interconnected channel networks that significantly influence groundwater flow dynamics. This literature review aims to synthesize current knowledge regarding the effects of karst on water circulation and permeability in carbonate aquifers based on hydrogeological, hydrochemical, geophysical, and numerical modeling studies from various regions worldwide. The review shows that karstification substantially enhances hydraulic conductivity and produces complex flow regimes ranging from diffuse fracture flow to turbulent conduit flow. The epikarst zone plays an important role in regulating infiltration and recharge distribution, while tectonic structures such as faults and fractures strongly control groundwater pathways and aquifer compartmentalization. Karst aquifers also exhibit strong spatial variability in permeability, making groundwater flow and contaminant transport difficult to predict using conventional hydrogeological approaches. In addition, the integration of equivalent porous medium (EPM), discrete fracture network (DFN), and conduit network (CN) models is essential for accurately representing karst aquifer behavior. Understanding the influence of karstification on groundwater circulation is therefore crucial for sustainable groundwater management and aquifer vulnerability assessment, particularly in regions facing increasing water demand and climate change pressures.
Abstract:Digital transformation has fundamentally reshaped healthcare service delivery worldwide, particularly in tertiary hospitals that rely heavily on integrated digital systems such as Electronic Health Records (EHRs), telemedicine,…
dicine, clinical decision support systems, and data-driven healthcare technologies. Despite rapid technological advancement, limited empirical evidence explains how healthcare professionals’ digital competence contributes to healthcare service performance within the context of healthcare transformation in Saudi Arabia. Previous studies have primarily focused on technological adoption or technical outcomes, while the psychological and organizational mechanisms underlying digital healthcare performance remain underexplored. Drawing upon the Job Demands–Resources (JD-R) Theory and Resource-Based View (RBV), this study investigates the influence of Digital Health Competence (DHC) on Healthcare Service Performance (HSP), examining the mediating role of Work Engagement (WE) and the moderating role of Organizational Support (OS). This study employed a quantitative cross-sectional explanatory design using Structural Equation Modeling–Partial Least Squares (SEM-PLS). Data were collected from 312 healthcare professionals at King Abdullah Medical City (KAMC), Saudi Arabia, selected through stratified random sampling. The study included physicians, nurses, pharmacists, and allied healthcare professionals actively utilizing digital healthcare systems in clinical practice. Measurement instruments were adapted from internationally validated scales, including the European Digital Competence Framework for Health Professionals, Utrecht Work Engagement Scale (UWES), and Perceived Organizational Support Scale. Data analysis included assessment of the measurement model, structural model evaluation, mediation analysis, moderation analysis, effect size (f²), predictive relevance (Q²), and model fit indices. The findings demonstrated that Digital Health Competence had a positive and significant effect on Healthcare Service Performance (β = 0.328, p < 0.001) and Work Engagement (β = 0.541, p < 0.001). Work Engagement significantly influenced Healthcare Service Performance (β = 0.462, p < 0.001) and partially mediated the relationship between Digital Health Competence and Healthcare Service Performance (β = 0.250, p < 0.001). In addition, Organizational Support significantly moderated the relationship between Digital Health Competence and Work Engagement (β = 0.217, p < 0.001). The structural model demonstrated substantial explanatory power (R² HSP = 0.683) and satisfactory predictive relevance. This study contributes theoretically by extending the application of JD-R Theory and RBV within the context of digital healthcare transformation in tertiary hospitals. The study proposes an integrated model demonstrating that digital competence functions not only as a technical capability but also as a strategic personal resource that enhances work engagement and healthcare service quality. Practically, the findings emphasize the importance of strengthening digital competency development, supportive organizational climates, and adaptive digital infrastructures to improve healthcare professionals’ performance and accelerate sustainable healthcare transformation in Saudi Arabia.
Abstract:This study discusses the implementation of the Naïve Bayes method to predict catering sales at PT.Negara Rasa Indonesia. The background of this study is based on the problem of suboptimal sales due to the absence of a structured…
tructured sales prediction system. The Naïve Bayes method was chosen because of its simplicity, speed, and ability to classify data with a high degree of accuracy. The data used in this study is historical sales data from the last two years, which has undergone cleaning, labeling, and transformation into four sales categories, namely very popular, popular, fairly popular, and less popular. The testing process was carried out using RapidMiner software by dividing the dataset into training data and test data at various ratios of 80:20. The test results showed a very high level of accuracy, with the highest value reaching 91.41%. These findings prove that the Naïve Bayes method is reliable for predicting catering sales, thereby assisting decision-making in more efficient sales management and planning at PT. Negara Rasa Indonesia.
Abstract:This study investigates the tensile uplift capacity of screw piles in clay soil as an alternative anchoring system for slope stabilization in cohesive ground conditions. The research aims to address the limited availability…
ity of empirical field data on screw-pile behavior under repeated loading and to evaluate the agreement between theoretical predictions and actual in situ responses. The methodology employs an experimental approach through in situ testing with screw-pile diameters of 10 cm, 15 cm, and 20 cm, and embedment depths ranging from 0.6 m to 1.0 m. The tests were conducted under both static and repeated tensile loading using a hydraulic jack system, accompanied by vertical deformation measurements to establish load–displacement curves. Theoretical capacity was calculated using a limit equilibrium approach for comparison with experimental results. The findings reveal a nonlinear load–displacement response, characterized by initial stiffness followed by progressive deformation into the post-yield stage. At a maximum load of 2.858 tons, deformation increased with diameter, from 5.10 cm (10 cm) to 8.49 cm (20 cm). Under repeated loading, failure occurred at a lower load of approximately 1.6 tons with a maximum deformation of 1.648 cm, indicating potential capacity degradation due to cyclic loading. The comparison between theoretical and field results shows significant deviations, with analytical predictions generally underestimating the in situ capacity. This highlights the limitations of simplified models that do not fully account for shaft adhesion, installation disturbance, soil heterogeneity, pore-water pressure effects, and cyclic degradation. Overall, this study contributes valuable field pull-out test data for screw piles in clay under repeated loading, emphasizing the need for design calibration based on full-scale testing for slope stabilization applications. The results also suggest opportunities for further research involving long-term monitoring and advanced modeling of cyclic degradation.
Abstract:This study specifically projects output and predicts economic growth, investment needs, and additional labor requirements sectorally, using labor and output data (GDP by business field at constant prices) for the period…
2001-2019. The analysis method used is labor projection based on the output approach, namely the Incremental Labor Output Ratio (ILOR). The results of the study show that (1) the increase in output in the agricultural sector does not have an impact on the expansion of labor absorption in the sector, but the conditions contrast with the increase in output in the public services, mining and trade sectors which will have an impact on the expansion of labor (2) Additional labor in the agricultural sector does not provide optimal results or additional labor in the agricultural sector and has an impact on decreasing output in the future (3) Additional labor in the mining sector will result in high output in the future.
Abstract:This study examines consumer behavior towards sustainable products, specifically investigating the influence of environmental attitudes and green product attributes on green purchase intention among Tanimbar Ikat Weaving…
consumers in Tanimbar Islands Regency. Employing a quantitative approach with Structural Equation Modeling-Partial Least Square (SEM-PLS) analysis through SmartPLS software, data were collected from 385 respondents selected via purposive sampling based on consumers who knew and had purchased Tanimbar woven products. The research tested direct relationships and moderating effects of premium price, education, and gender variables. Results revealed that environmental attitudes (β = 0.349; t = 5.306; p = 0.000) and green product attributes (β = 0.207; t = 3.014; p = 0.003) significantly and positively influence green purchase intention, with the model explaining 60.7% of the variance (R² = 0.607) and demonstrating strong predictive relevance (Q² = 0.539). However, the three moderating variables—premium price, education, and gender—did not significantly strengthen or weaken these relationships, indicating that environmental consciousness and product perception remain dominant factors regardless of demographic or economic considerations. These findings provide practical implications for traditional craft entrepreneurs in developing sustainability-based marketing strategies and empowering the local creative economy, while contributing to the sustainable development goals through cultural preservation and environmental conservation in Indonesia's eastern region.
Abstract:Amidst a digitized business landscape, Digital Leadership (DL) has emerged as a crucial predictor of Team Performance. However, a fundamental question arises: which dimensions of digital leadership truly drive performance…
e technical skills (tech-savviness), strategic vision, or relational skills? This study uses a Systematic Literature Review (SLR) of 51 articles to deconstruct digital leadership into four main dimensions: (1) Technological, (2) Visionary-Strategic, (3) Relational-Emotional, and (4) Structural-Managerial. The findings reveal an unexpected pattern: the technological dimension only acts as a hygiene factor, while the structural-managerial and visionary-strategic dimensions show the most consistent impact on team performance. Furthermore, the effectiveness of the relational dimension is highly context-dependent, strong in small Agile teams but NOT significant in large bureaucratic organizations. These findings suggest a reframing of the conventional assumption that “digital leaders” must start with technical expertise, and instead suggest that organizations should train digital talent in soft skills and strategic vision, or train existing visionary leaders in basic digital literacy.
Abstract:Coal mining, handling, and transportation activities are major sources of airborne particulate matter containing respirable crystalline silica, which poses significant risks to respiratory health. Silicosis remains a serious…
ious occupational and environmental disease affecting not only workers but also communities living near coal-handling areas. Physical environmental factors, including air quality, temperature, humidity, and wind speed, play an important role in influencing dust generation, dispersion, and inhalation exposure. This narrative review aims to synthesize current evidence on the influence of physical environmental conditions on silica exposure and silicosis development, integrating findings from environmental monitoring studies, epidemiological research, and experimental Wistar rat models. A literature search was conducted using major scientific databases to identify relevant peer-reviewed articles published between 2010 and 2024. The reviewed evidence indicates that prolonged or high-intensity exposure to silica dust is strongly associated with chronic pulmonary inflammation and progressive fibrosis. Environmental conditions can exacerbate exposure risk by increasing airborne particulate concentrations and respiratory vulnerability. Experimental studies using Wistar rats provide mechanistic insights into silica-induced lung injury, supporting epidemiological observations in human populations. This review highlights the importance of integrating environmental, occupational, and biological perspectives to improve risk prediction, early detection, and preventive strategies for silicosis in coal-handling regions.