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This study analyzes the effect of logistics digitalization systems and personnel competence on the distribution of personnel uniforms (kaporlap) at Kodiklatal. The study was motivated by the fact that the distribution system had not yet operated optimally despite the implementation of digital logistics, while delays in updating the Sistem Informasi Entitas Samapta (SIMBENSAM), limited documentation of device identities, and unequal digital skills among personnel still constrained distribution performance. A quantitative approach with explanatory design was applied. The population consisted of 3,099 personnel and the sample comprised 97 respondents selected using Slovin's formula. Data were collected through Likert-scale questionnaires and internal documentation, then analyzed using validity and reliability tests, classical assumption tests, descriptive analysis, and simple and multiple linear regression. The results show that the logistics digitalization system has a positive and significant effect on kaporlap distribution (t = 24.607; p < 0.05), personnel competence also has a positive and significant effect (t = 37.972; p < 0.05), and both variables simultaneously affect distribution performance (F = 788.285; p < 0.05) with an R square of 0.944. These findings confirm that digital systems and human competence must be strengthened in an integrated manner to support efficient, accurate, and timely distribution in a military education environment.

Political disinformation has become one of the most critical challenges in contemporary digital democracies due to the rapid expansion of social media ecosystems. This study investigates the effectiveness of machine learning approaches in detecting political disinformation across online platforms such as Twitter, Facebook, and political discussion forums. Using a qualitative research design with a content analysis approach, the study examines linguistic manipulation, emotional narratives, sentiment polarity, and behavioral communication patterns embedded in misleading political content. The findings indicate that deep learning models, particularly Long Short-Term Memory (LSTM) architectures, demonstrate superior performance in identifying contextual and semantic inconsistencies compared to traditional machine learning algorithms. The study also reveals that algorithmic amplification, echo chambers, and coordinated bot activities significantly contribute to the rapid spread of political misinformation. Furthermore, the research highlights the importance of ethical artificial intelligence governance, transparency, and digital literacy in strengthening democratic resilience and protecting information integrity within digital communication environments

The drainage system is critical infrastructure for managing stormwater runoff in densely built urban areas, including higher education institutions. This study aims to evaluate the capacity performance of the existing drainage channels in the UPN "Veteran" Jawa Timur campus area. The evaluation was conducted through two main stages: hydrological analysis using the rational method to estimate the design runoff discharge for a 10-year return period, and hydraulic analysis using Manning's equation to calculate the channel cross-sectional capacity in accordance with Permen PU No. 12 of 2014. Based on the assessment of 43 drainage channels, the results showed that 33 channels (76.7%) are still functioning optimally and capable of accommodating the design discharge. Conversely, 10 channels (23.3%) were identified as having insufficient capacity. This capacity deficit was triggered by initial designs that did not accommodate the 10-year return period flood discharge, increased runoff coefficients due to massive pavement development, and effective cross-section narrowing caused by sedimentation. To mitigate inundation issues, this study recommends redesigning the failing channels using an economical hydraulic cross-section, accompanied by periodic normalization and dredging for functional channels. The findings of this study are expected to serve as technical guidelines for the optimal and sustainable management of campus drainage infrastructure.

The coffee shop industry has experienced substantial growth in recent years, creating intense competition that compels businesses to continuously enhance service performance in order to maintain customer satisfaction and market competitiveness. PT Jokopi Indonesia Group has encountered several service-related issues reflected in declining sales performance and recurring customer complaints, indicating the need for a comprehensive evaluation of service quality. This study aims to identify service attributes that fail to meet customer expectations and determine improvement priorities through the integration of the SERVQUAL and Kano methods. A quantitative approach was employed using questionnaire data collected from 50 customers who had prior experience with the company’s services. SERVQUAL was utilized to assess discrepancies between customer expectations and perceived service performance, while the Kano model was applied to classify attributes according to their contribution to customer satisfaction. The findings reveal that all evaluated attributes generated negative gap values, indicating that existing service performance has not yet reached the level expected by customers. The most critical gaps were identified in menu availability, air-conditioning and fan comfort, payment convenience, and straw availability. Kano classification further demonstrates that menu availability and thermal comfort facilities belong to the Must-Be category, meaning that failure to provide these attributes may trigger significant customer dissatisfaction. The integration of SERVQUAL and Kano highlights these attributes as the most urgent areas for improvement. The results provide managerial guidance for developing targeted service enhancement initiatives aimed at strengthening customer satisfaction, retention, and competitive advantage.

This research investigates the integration of Sound Governance principles within the sustainable tourism policy cycle as a mechanism to mitigate institutional fragmentation and evaluation inefficiencies in developing economies. Adopting a sequential explanatory mixed-methods design, the study establishes a multidimensional evaluation framework congruent with the Sustainable Development Goals (SDGs). Policy performance is rigorously analyzed across five strategic domains: Economy, Social-Welfare, Culture-Education, Environment, and Governance. The quantitative methodology employs 17 adapted SDG indicators to assess policy efficacy, while the subsequent qualitative phase utilizes semi-structured interviews and stakeholder mapping to deconstruct complex power dynamics within multi-actor co-management structures. The empirical findings demonstrate that Sound Governance—predicated on transparency and accountability—acts as a fundamental catalyst for policy effectiveness. It significantly enhances destination sustainability through a structured input-process-output-outcome-impact pathway. Evidence from the case study of Penglipuran Village, Bali, validates these results, showing that while indigenous institutional legitimacy bolsters social responsiveness, it remains susceptible to economic dependencies driven by overtourism. Ultimately, this study asserts that embedding SDGs into the policy evaluation cycle elevates assessments from perfunctory administrative exercises to strategic instruments essential for ecosystem preservation and long-term demand stability. These insights establish Sound Governance as a strategic intangible asset, providing significant theoretical contributions to development administration and offering pragmatic frameworks for policy-makers managing sustainable destinations in competitive global markets.

The quality of life and well-being of women in Indonesia can be measured through the Female Life Expectancy indicator. Data on Female Life Expectancy from 2022 to 2024 shows a nationally positive trend; however, a significant disparity persists across provinces, particularly between the Western and Eastern regions of Indonesia. The nation still faces challenges in ensuring an equitable quality of life for women, as evidenced by the national Female Life Expectancy (FLE) in 2024 at 74.21 years, which remains lower than ASEAN counterparts such as Singapore at 83.86 years. Furthermore, regional imbalances are reflected in the performance gap between D.I. Yogyakarta (77.4 years) and West Sulawesi (68.28 years). This study aims to analyze the effects of Women's Income Contribution, Access to Clean Water, the Number of Families Receiving Social Assistance, and Women's Mean Years of Schooling on Female Life Expectancy in Indonesia during the 2022–2024 period. The estimation method applied in this research is the Fixed Effect Model (FEM) via a quantitative panel data regression approach, spanning an observation area of 33 provinces (n=99). Based on the analysis, Female Life Expectancy is proven to be positively and significantly influenced by Women's Mean Years of Schooling and Access to Clean Water. These findings indicate that human resource quality and environmental conditions serve as dominant factors in driving up Female Life Expectancy. Therefore, government policy interventions should ideally focus on expanding educational access for women and ensuring the equitable distribution of clean water infrastructure.

This study investigates the role of Baitul Maal wa Tamwil (BMT) in empowering Micro, Small, and Medium Enterprises (MSMEs) through the integration of Maqashid Sharia principles and financial inclusion strategies. Despite the strategic importance of MSMEs in economic growth and poverty reduction, many face challenges in accessing formal financial services. BMT, with its dual function of social (maal) and commercial (tamwil) activities, offers a unique platform to bridge this gap. Using a qualitative systematic literature review guided by PRISMA, this study analyzes 30 relevant articles to examine BMT operational models, implementation of Maqashid Sharia objectives, financial inclusion practices, and their impact on MSME performance. Findings indicate that BMT effectively supports MSMEs in capital access, income generation, and business resilience, but inconsistencies in balancing social and commercial objectives limit. holistic empowerment. Integrating Maqashid Sharia principles enhances ethical and sustainable outcomes, while financial inclusion expands outreach to underserved entrepreneurs. Optimization strategies, including strengthening institutional capacity, combining financial and non-financial support, and context-specific interventions, are essential for maximizing BMT effectiveness. This study contributes a comprehensive framework linking ethical, financial, and empowerment dimensions, offering practical guidance for policymakers and BMT managers in promoting inclusive and sustainable MSME development.

In an increasingly competitive business environment, particularly within the tourism industry, an organisation's ability to innovate and design effective strategic planning has become a critical factor in sustaining and improving organisational performance. This study aims to analyse the effect of innovation and strategic planning on organisational performance at Kampung Coklat Blitar Educational Tourism. This study employed a quantitative approach, with data collected through questionnaire distribution involving 53 respondents. The sampling was conducted using a saturated sampling technique (census), in which all members of the population were used as research samples. The sampling criteria consisted of senior-level active employees with a minimum of eight years of work experience and managers at Kampung Coklat Blitar Educational Tourism. Data analysis was carried out using the SPSS software. The results of the study indicate that innovation has a positive and significant effect on organisational performance with a P-value of 0.006 and a T-statistic of 2.869. Furthermore, strategic planning also has a positive and significant effect on organisational performance with a P-value of < 0.001 and a T- statistic of 5.573.

This study aims to determine the influence of work environment and work motivation on employee performance at PT. Bahari Bahagia Ria Jambi. This study uses quantitative methods. The population and sample in this study were all employees of PT. Bahari Bahagia Ria Jambi, totaling 76 respondents using saturated sampling techniques. The analysis method uses descriptive analysis. Instrument testing by conducting Validity Test and Reliability Test, also with Multiple Linear Regression and Classical Assumption Test. Hypothesis testing with t-test (Partial Test) and f-test (Simultaneous Test) using SPSS tools. The results of this study indicate that the performance description is in the very high category, the work environment is in the very supportive category and work motivation is in the very motivated category. The work environment has a positive and significant effect on employee performance at PT. Bahari Bahagia Ria Jambi, work motivation has a positive and significant effect on employee performance and simultaneously (simultaneously) the work environment and work motivation have a positive and significant effect on employee performance. The suggestions from this research are: (1) Employees should always maintain good relationships with each other so that the company's goals can be realized (2) Leaders should always provide encouragement so that employees can carry out their duties well (3) Companies should always pay attention to the potential of their employees and the efforts made to develop this potential through training.

Conflict is an inevitable phenomenon in educational environments due to differences in characteristics, interests, perceptions, and goals among school members. If not managed properly, conflict can disrupt the learning process, weaken social relationships, and negatively affect educational quality. This study aims to analyze the role of collaborative conflict management in improving the quality of education in madrasahs and schools. The research employed a qualitative approach using a library research method by reviewing various books, scientific journals, and relevant literature related to conflict management and education. The findings indicate that collaborative conflict management, implemented through effective communication, deliberation, discussion, negotiation, and cooperation, can facilitate constructive and sustainable conflict resolution. Furthermore, the application of collaborative conflict management contributes to strengthening cooperation among school members, creating a harmonious and conducive learning environment, and improving teacher performance as well as student learning outcomes. School principals play a strategic role as mediators and facilitators in guiding conflict resolution processes fairly and participatively. Therefore, collaborative conflict management can serve as an effective strategy for enhancing educational quality and fostering a positive educational climate in madrasahs and schools.

The development and performance of high-strength, environmentally friendly, and renewable nunang fiber (Cordia dichotoma)-reinforced polyester composites continue to be refined to achieve optimal performance. This study characterizes the key properties of nunang fiber-reinforced polyester composites with carbon powder fillers. The polyester composites were fabricated using a hot-press method with a nunang fiber volume fraction of 20% (by weight) and varying carbon powder content from 0–10% (by weight). The results of the investigation show that the tensile and bending strengths of the composites increase with increasing carbon powder content up to 2.5%. However, adding carbon powder filler up to 10% to the polyester–nunang fiber composites reduces their tensile and bending strengths. A different trend is observed for the impact toughness of the composites, which increases up to a carbon powder content of 5% and decreases when the carbon powder content reaches 10%. This phenomenon is attributed to the ability to form an optimal fiber-matrix interface between the nunang fibers and the polyester–carbon powder matrix. SEM morphological observations confirmed fiber pull-out failure and matrix failure due to the high stiffness caused by the presence of the carbon powder filler.

The development of digital services by BPJS Ketenagakerjaan through the JMO (Jamsostek Mobile) application has triggered a surge in large-scale and unstructured user reviews on the Google Play Store, thereby complicating manual analysis and conventional sentiment analysis in accurately identifying specific issues. This research aims to implement the Aspect-Based Sentiment Analysis (ABSA) method to granularly evaluate JMO application reviews based on specific aspects, while simultaneously addressing class imbalance and computational efficiency issues. The proposed method combines the pretrained IndoBERT model as a contextual feature extractor, the SMOTE technique to balance the training data, and an artificial neural network (Neural Network) as the classification layer without performing full fine-tuning. The dataset used consists of 90,268 unique reviews categorized into five main aspects through keyword matching, namely General Satisfaction/Complaints, Performance & Stability, Service & Support, Feature Quality, and UI/UX, with initial lexicon-based labeling using the InSet Lexicon. The research results indicate that the proposed model successfully achieves highly optimal performance with an accuracy rate of 91.81% and a weighted F1-score of 92%. Furthermore, the implementation of SMOTE proved effective in enhancing model reliability on the minority class (negative sentiment), achieving an F1-score of 89%. The implications of this research contribute an accurate and efficient aspect-based sentiment analysis framework for developers, and serve as a strategic evaluation tool for BPJS Ketenagakerjaan in mapping specific user complaints to accelerate continuous improvements in the performance, stability, and service quality of the JMO application.

This study aims to examine the implementation of policies regarding the use of the e-Kelurahan feature in the Sangu Palu application in Taipa Village. The study employs George C. Edward III’s policy implementation theory, which consists of four dimensions: communication, resources, disposition, and bureaucratic structure. A qualitative descriptive approach was used, with data collected through observation, in-depth interviews, documentation, and literature review involving nine informants. The findings indicate that the implementation of the e-Kelurahan policy has not yet run optimally. The main obstacle lies in the communication aspect, particularly the lack of direct public socialization regarding the use of the application, resulting in low public understanding and limited utilization of digital services. In addition, training for village officials has not been conducted continuously, as it was only provided during the initial implementation stage. Therefore, periodic retraining is needed to improve technical competence and evaluate service performance. Although the aspects of disposition and bureaucratic structure have generally functioned well, they have not been sufficient to optimize digital service utilization. These findings are consistent with the Electronic-Based Government System (SPBE) evaluation results, which place Palu City in the “sufficient” category, indicating the need for further improvement in digital service implementation.

Aerobic capacity, commonly measured by maximal oxygen uptake (VO₂max), is a key indicator of physical fitness and athletic performance, particularly in endurance sports. Recent attention has focused on the role of respiratory muscle function in supporting exercise performance, as respiratory muscle fatigue during high-intensity or prolonged activity may reduce ventilatory efficiency and exercise tolerance. This literature review aims to examine current evidence regarding the effects of Respiratory Muscle Training (RMT), including Inspiratory Muscle Training (IMT), on aerobic capacity in athletes. Relevant studies were identified through electronic databases such as PubMed, Scopus, and Google Scholar using keywords related to respiratory muscle training, VO₂max, and athletes. The reviewed studies generally reported improvements in inspiratory muscle strength, reduced respiratory muscle fatigue, and enhanced ventilatory efficiency following RMT interventions. These physiological adaptations may contribute to better exercise tolerance and overall athletic performance. However, evidence regarding direct improvements in VO₂max remains inconsistent across studies. The findings suggest that RMT can be used as a complementary strategy alongside conventional training programs to support aerobic performance. In addition, improved respiratory muscle function may provide benefits in health promotion and rehabilitation by reducing dyspnea and increasing exercise tolerance. Further well-designed studies are needed to clarify the extent of RMT’s contribution to improving VO₂max in athletic populations.

Aerobic capacity, commonly measured by maximal oxygen uptake (VO₂max), is a key indicator of physical fitness and athletic performance, particularly in endurance sports. Recent attention has focused on the role of respiratory muscle function in supporting exercise performance, as respiratory muscle fatigue during high-intensity or prolonged activity may reduce ventilatory efficiency and exercise tolerance. This literature review aims to examine current evidence regarding the effects of Respiratory Muscle Training (RMT), including Inspiratory Muscle Training (IMT), on aerobic capacity in athletes. Relevant studies were identified through electronic databases such as PubMed, Scopus, and Google Scholar using keywords related to respiratory muscle training, VO₂max, and athletes. The reviewed studies generally reported improvements in inspiratory muscle strength, reduced respiratory muscle fatigue, and enhanced ventilatory efficiency following RMT interventions. These physiological adaptations may contribute to better exercise tolerance and overall athletic performance. However, evidence regarding direct improvements in VO₂max remains inconsistent across studies. The findings suggest that RMT can be used as a complementary strategy alongside conventional training programs to support aerobic performance. In addition, improved respiratory muscle function may provide benefits in health promotion and rehabilitation by reducing dyspnea and increasing exercise tolerance. Further well-designed studies are needed to clarify the extent of RMT’s contribution to improving VO₂max in athletic populations.

Stunting is a multifactorial public health problem influenced by various risk factors that may emerge during the prenatal period. Early identification of stunting risk during pregnancy is important to support preventive interventions. This study aimed to develop a stunting risk prediction model based on maternal prenatal factors using the Random Forest algorithm. Secondary data from 172 pregnant women, consisting of 83 stunting cases and 89 non-stunting cases, were analyzed. The predictor variables included maternal age during pregnancy, height, hemoglobin level, mid-upper arm circumference (MUAC), smoking history, hypertension, asthma, and diabetes mellitus. The research stages consisted of data preprocessing, model training using Stratified 5-Fold Cross Validation, performance evaluation, external testing, and feature importance analysis. Internal evaluation results showed an accuracy of 60%, precision of 60.6%, recall of 57.3%, F1-score of 58.9%, and AUC of 0.6688. External testing yielded an accuracy of 70% and an AUC of 0.6167. Feature importance analysis identified maternal age during pregnancy as the most influential variable in the prediction process. The findings indicate that maternal prenatal factors have potential for early stunting risk identification, although the predictive performance remains moderate. This approach may serve as a foundation for developing early screening tools to support targeted interventions among high-risk pregnancies.

The rapid development of information technology drives various business sectors, including the beauty and health industry, to adopt digital systems in their operational management. A Beauty Clinic, a medium-scale aesthetic clinic, faces significant operational challenges in managing human resources, finance, and digital marketing in an integrated manner. This study aims to analyze the existing manual operational system of A Beauty Clinic using the PIECES framework (Performance, Information, Economy, Control, Efficiency, Service), design and configure an Odoo ERP Community Edition implementation integrating the HR, Invoicing/Point of Sale, and Social Marketing modules, and evaluate the operational efficiency improvements achieved. The research employed a qualitative descriptive approach with a case study method and Rapid Application Development (RAD) as the system development methodology. Data was collected through direct observation and semi-structured interviews. The results show that the manual system experienced critical problems across all six PIECES dimensions. Post-implementation evaluation indicates an estimated 80% reduction in the secretary's administrative workload (from 20–25 hours to 3–5 hours per month), over 90% reduction in payroll error frequency, and an 87% reduction in transaction processing time per cashier transaction. The implementation of role-based access control and complete audit trails fundamentally addressed the security vulnerabilities identified in the as-is analysis. This study demonstrates that Odoo Community Edition is an effective, comprehensive, and cost-efficient ERP solution for small and medium-scale beauty clinics seeking to transform from fragmented manual systems to integrated, data-driven information systems.

This study aims to analyze the effect of homework load and extended study hours on students’ learning stress levels. The background of this research is based on increasing academic demands that may affect students’ psychological conditions. This study employs a qualitative approach with data collected through observation and interviews. The results indicate that excessive homework load and prolonged study duration significantly contribute to higher levels of learning stress. Students tend to experience physical and mental fatigue, decreased motivation, and difficulty managing time between study and rest. In addition, pressure to achieve high academic performance further exacerbates stress levels. Other factors such as lack of environmental support and less varied teaching methods also influence students’ stress. Furthermore, students often report feelings of anxiety and emotional exhaustion when academic tasks accumulate without adequate rest periods. This condition not only affects their psychological well-being but also reduces concentration and learning effectiveness in the classroom. Therefore, balanced learning load management, appropriate task distribution, and more effective and humanistic teaching strategies are needed to reduce learning stress and improve the quality of education. Schools and educators are encouraged to consider students’ cognitive capacity and mental health in designing assignments and study schedules to create a more supportive learning environment.

This study aims to: (1) describe Employee Performance, Work Climate, and Employee Engagement; and (2) analyze the influence of Work Climate and Employee Engagement on Employee Performance, both partially and simultaneously. The population of this study consisted of all employees of the Ministry of Religious Affairs Office of Sikka Regency, totaling 189 employees. Since the population size was relatively large, the sampling technique used was probability sampling with a simple random sampling method. The sample size was determined using the Slovin formula, resulting in 65 respondents. Data were collected through questionnaires and analyzed using descriptive and inferential statistical methods, namely multiple linear regression analysis. Hypothesis testing was conducted using the F-test and t-test. The results of the descriptive analysis indicate that Employee Performance is categorized as good, Work Climate is categorized as good, and Employee Engagement is also categorized as good. The results of the t-test show that Work Climate has a positive and significant effect on Employee Performance. Furthermore, Employee Engagement also has a positive and significant effect on Employee Performance. The results of the F-test indicate that Work Climate and Employee Engagement simultaneously have a significant effect on Employee Performance. The coefficient of determination analysis shows that the two independent variables in this study are able to explain 47.9% of the variation in Employee Performance at the Ministry of Religious Affairs Office of Sikka Regency.

Agentic artificial intelligence (AI) systems capable of autonomous goal-directed behavior, multi-step planning, tool use, multi-agent coordination, and iterative self-correction represent a transition from passive clinical AI tools toward systems that can participate in complex healthcare workflows. However, empirical evidence remains fragmented across clinical decision support, patient monitoring, and administrative applications, and no systematic synthesis has evaluated which agentic principles have been technically demonstrated and which have accumulated sufficient evidence to support responsible clinical deployment. We conducted a PRISMA-informed systematic review of peer-reviewed empirical studies published between January 2025 and April 2026. Searches across five bibliographic databases and Google Scholar, supplemented by citation tracking, identified 443 unique records for screening, of which 25 met the predefined PICOS and quality appraisal criteria. Evidence was synthesized using an evidence-informed seven-principle framework derived from the integration of agentic AI, clinical AI, and healthcare governance literature. This framework provides a structured lens for examining how agentic principles are evaluated individually and in combination, enabling a deployment-readiness perspective that extends beyond capability-focused assessments alone. The evidence base was concentrated on technical capability principles, whereas human oversight, safety, compliance, and equity-related evaluation received comparatively limited attention. Most studies remained at the laboratory, benchmark, or proof-of-concept stage, and none reported demographic-stratified performance outcomes. Overall, the findings suggest a structural asymmetry in agentic healthcare AI: empirical research is advancing agentic capabilities more rapidly than it is generating evidence for the oversight, safety, equity, and governance mechanisms required for responsible clinical translation.