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Gestational Diabetes Mellitus (GDM) is a pregnancy-related metabolic disorder that poses health risks to both mother and fetus if not detected early, requiring accurate prediction methods for early screening and clinical decision-making. This study applies the Random Forest algorithm to detect GDM risk using clinical data from the Pima Indian Dataset. Data preprocessing included handling missing values, standardization, feature engineering, and a 70:30 train–test split. Two models were developed: a baseline and an optimized model using GridSearchCV hyperparameter tuning, validated with 5-fold cross-validation. Performance was assessed using a classification report, confusion matrix, and ROC–AUC. Results show that the optimized model outperforms the baseline, achieving 88% accuracy, an AUC of  93%, and average recall of 81%–85%. Compared to previous studies, this approach demonstrates improved predictive performance. The findings indicate that combining Random Forest with comprehensive preprocessing, feature engineering, and model optimization is effective and feasible for developing a medical decision support system for early GDM risk screening.

Manual quality assessment of Platelet Concentrate (TC) is highly subjective and inconsistent, necessitating an objective, automated classification system. This study aims to develop a computationally efficient, low-cost model for TC quality classification using Histogram Features extracted from grayscale images combined with the K-Nearest Neighbor (KNN) algorithm. The methodology employed critical preprocessing steps, including StandardScaler for normalization and SMOTE for balancing the training data, followed by optimization across K=1 to K=30. The optimal model achieved a maximum accuracy of 69.23% at K=6, with an F1-Score of 71.43%, confirming robust performance on the imbalanced testing set. The results validate the effectiveness of the Histogram-KNN approach as a consistent and reliable decision support system for rapid TC quality screening in resource-limited settings.

This study aims to analyze in-depth the interest of the Setro Village community in choosing PNM Mekaar Syariah financing as a source of capital for micro and small enterprises (MSMEs). This phenomenon is interesting because it shows how economic, social, and spiritual factors contribute to the financial decisions of rural communities. This research was conducted using a qualitative exploratory approach, using case studies and in-depth interviews with key informants. To explain the relationship between attitudes, subjective norms, and behavioral control on community intentions to choose Islamic financing, data analysis was conducted thematically. The Theory of Planned Behavior (TPB) framework was also used. The study shows that positive community perceptions of ease of access, economic benefits, and compliance with Islamic principles are the main factors shaping community interest in PNM Mekaar Syariah. Fast, easy, and uncomplicated financing increases consumer trust and enhances perceived behavioral control. Conversely, increased business capital and family income enhance the sustainability of micro-enterprises. The institution is given moral legitimacy and spiritual conviction by the implemented Islamic values, such as the yield system and the freedom from usury. Community participation decisions are also driven by social factors such as group support, advice from group leaders, and the quality of service provided by field officers. Theoretically, this study adds local religiosity and socio-cultural aspects to enrich the application of the Theory of Planned Behavior in the context of rural Islamic finance.

The development of military communication technology requires effective, secure, and adaptable communication systems suitable for training and operational environments. During the implementation of Karkata Yudha Practical Training, Marine Corps cadets still experience various communication constraints due to the limitations of conventional communication devices that do not support hands-free operation, noise resistance, and communication confidentiality. This study aims to analyze the utilization of Tactical Radio Person Headsets as a communication support tool to enhance the effectiveness and efficiency of Karkata Yudha practical training for Marine Corps cadets. This research employed a qualitative method with a descriptive-analytical approach. Data were collected through direct observation of training activities, in-depth interviews with communication experts from the Marine Corps, and documentation studies. Data analysis was conducted using SWOT analysis to identify strengths, weaknesses, opportunities, and threats related to the implementation of Tactical Radio Person Headsets. The results indicate that the utilization of Tactical Radio Person Headsets significantly improves tactical communication quality, accelerates coordination among units, and supports maneuver execution and decision-making in the field. The challenges identified include limited equipment availability, procurement costs, and the need for technical training for users. Overall, Tactical Radio Person Headsets demonstrate strong potential to be integrated into Marine Corps cadet training systems to enhance operational readiness and professionalism in the future.

This study analyzes the strategic role of digital transformation in accelerating the development of the green economy in Azerbaijan. As global economic systems shift toward sustainability-oriented models, Azerbaijan has begun integrating digital technologies—such as smart energy systems, geographic information platforms, and digital monitoring tools—into its environmental and economic policies. These initiatives are designed to reduce carbon intensity, enhance resource efficiency, and modernize industrial sectors in alignment with international climate standards. The study employs a qualitative library-based approach supported by content analysis to assess state programs, institutional reforms, and policy documents related to digital governance and renewable energy deployment. The findings indicate that digital solutions facilitate transparent decision-making, optimize energy consumption, and support ecological innovations, making them essential components of Azerbaijan’s national development agenda. However, the transition remains constrained by infrastructural disparities, limited technological competencies, and regulatory gaps. The study argues that sustainable development goals cannot be fully realized without comprehensive digital integration, institutional coordination, and capacity-building initiatives. Thus, digitalization is not merely a supportive tool but a foundational mechanism for the advancement of the green economy and long-term socio-economic transformation in Azerbaijan.

In today's digital era, recommendation systems have become an integral part of supporting consumer purchasing decisions, including in the food and beverage industry. This study aims to develop a product recommendation system for snacks and beverages using the item-based collaborative filtering method. This method was chosen due to its ability to handle large-scale user and product data, as well as its efficiency in providing relevant recommendations based on user consumption patterns. In this study, the system calculates the average user rating and implements   Cosine Similarity to measure the similarity between products, resulting in more accurate recommendations. The system also evaluates the accuracy of recommendations using the Mean Absolute Error (MAE) metric. Based on the results obtained, which is 0.285403 for the average error on 17 items, the developed recommendation system can improve consumers' shopping experience, help them find products that suit their tastes, and support the sales of snacks and beverages products in the market

The disparity in the quality of rehabilitation services across regional work units presents a significant challenge to effective public management. This study aims to bridge the gap between problem diagnosis and policy prediction by proposing a hybrid, data-driven approach. We integrate K-Means Clustering to map the current state of service quality and Stochastic Simulation to predict the impact of strategic interventions. Using the 2024 Public Satisfaction Index (IKM) dataset from the National Narcotics Agency (BNN), the K-Means algorithm initially identified 26 work units (15.7%) in the "Red Zone" (critical performance), highlighting urgent areas for improvement. Next, a stochastic simulation modeling a "Directed Priority Intervention" scenario was run. The results predicted a significant structural shift in the distribution of service quality, characterized by an 80.8% decrease in critical units (down to 5 units) and a 71.8% increase in excellent performing units (up to 67 units). These findings validate that the integration of clustering and simulation provides a comprehensive framework for evidence-based decision-making, enabling policymakers to optimize resource allocation and efficiently accelerate national service standardization.

This study explores the conceptual integration of Environmental, Social, and Governance (ESG) reporting and data analytics within the framework of sustainable digital accounting, with Industry 5.0 acting as a moderating paradigm. As organizations increasingly face demands for transparency, ethical governance, and sustainable operations, the limitations of traditional accounting systems have become evident. ESG reporting plays a crucial role in communicating non-financial performance and guiding strategic decisions aligned with stakeholder interests and regulatory expectations. However, the effectiveness of ESG disclosures is often hindered by fragmented data structures, inconsistent standards, and insufficient technological support. Data analytics, when integrated into ESG processes, enhances the precision, timeliness, and reliability of sustainability disclosures through predictive modeling, anomaly detection, and real time performance monitoring. Yet, despite its potential, the adoption of data analytics in accounting remains limited and under-theorized. Industry 5.0 introduces a human centric approach to technological transformation, emphasizing ethical innovation, inclusivity, and resilience. By positioning Industry 5.0 as a contextual and moderating framework, this study offers a novel perspective on how ESG and data analytics can synergize to create ethically aligned, future-ready accounting systems. Employing a systematic literature review, the research develops a conceptual model linking ESG, data analytics, and Industry 5.0, providing insights for academics, practitioners, and policymakers aiming to embed sustainability into digital accounting systems. The findings underscore the importance of aligning digital tools with ethical and societal values to advance accountable and sustainable business practices..    

Fortuna Furniture still manages its inventory manually, which causes many problems, including delayed reports, inaccurate information, and the potential for lost records. These issues affect the quality of decision-making and operational efficiency. This service aims to build a web-based inventory information system that improves speed, accuracy, and integration in inventory management. The system development process follows the Waterfall model SDLC approach, with requirements analysis, design, implementation, and testing supported by interviews, observation, and documentation. The results of the activity show that the developed system can reduce input errors, speed up the process of recording incoming and outgoing goods, and enable real-time stock monitoring. Additionally, the report generation process becomes more efficient and easier for management to access. Overall, the use of this information system significantly improved the efficiency of Fortuna Furniture's inventory management and demonstrated the importance of digitalization in helping businesses run more smoothly.

Penelitian ini bertujuan untuk mengembangkan sistem pendukung keputusan yang dapat membantu tim Marketing Officer (MO) PT. Alvarel Technology Innovation dalam menentukan status pelanggan secara objektif dan terstruktur. Sistem ini dirancang menggunakan kombinasi metode Analytical Hierarchy Process (AHP) dan Weighted Sum Model (WSM). Metode AHP digunakan untuk menentukan bobot kriteria yang meliputi Potensial Pasar, Urgensi, Finansial, serta Hubungan dan Reputasi, dengan memastikan konsistensi matriks perbandingan berpasangan. Hasil pembobotan kemudian digunakan dalam metode WSM untuk melakukan perhitungan skor total pelanggan dan menyusun pemeringkatan status berdasarkan nilai tertinggi hingga terendah. Data penelitian diperoleh dari catatan internal perusahaan dan wawancara dengan Marketing Officer, dengan jumlah sampel 30 pelanggan. Hasil pengujian menunjukkan bahwa sistem dapat menghasilkan peringkat status pelanggan dalam lima kategori, yaitu potensial, prospek, pending, pasif, dan skip. Temuan utama memperlihatkan bahwa kategori prospek memperoleh skor tertinggi dan menjadi prioritas tindak lanjut. Dengan demikian, sistem pendukung keputusan berbasis AHP–WSM ini mampu mengurangi subjektivitas, meningkatkan efisiensi, serta memberikan rekomendasi yang lebih akurat dan terukur untuk mendukung pengambilan keputusan strategis perusahaan dalam pengelolaan pelanggan.

This service activity was carried out in the Domestic Trade Sector, Central Java Provincial Industry and Trade Office with the aim of supporting the data collection process and updating the prices of basic necessities. This activity focuses on providing accurate and up-to-date price data as the basis for making price stabilization policies by local governments. The implementation of activities includes observation of the internal data collection system, daily price data input, data validation, and preparation of price development reports. In addition, the service team also coordinates with field officers and market managers to ensure the completeness of information and consistency of the data received. The technical assistance process related to the use of data collection application tools is also carried out to improve the competence of apparatus in managing information more effectively. The results of the activity show that systematic data updates are able to improve administrative efficiency, database accuracy, and support decision-making processes related to regional economic stability. Furthermore, the availability of more reliable price data allows local governments to detect potential price fluctuations early and formulate more timely and targeted intervention steps.

Murder committed by children presents a dilemma in the criminal justice system, as it must balance the enforcement of justice with the protection of children's rights. This article examines the problematic nature of juvenile criminal liability in murder by comparing the perpetrator's legal approach to that of adults. Normative juridical research methods are used to explain legal provisions, court decisions, and related doctrines. The results indicate that juvenile offenders are not solely focused on their culpability but also on the child's psychological capabilities, maturity level, and social circumstances. Meanwhile, adult offenders are held fully accountable, with a focus on punishment. The main challenges are the difficulty of proving intent and the need for special mechanisms for handling juvenile offenders of serious crimes. This study provides for strengthening the capacity of law enforcement, improving child rehabilitation facilities, optimizing diversion mechanisms, and educating the public to support humane and proportional protection and enforcement of justice.

This research is motivated by the importance of managerial skills in improving business productivity and efficiency, particularly in the entrepreneurial sector, which faces the challenges of competition, market changes, and limited resources. The objective of this study is to analyze the role of managerial skills development and its contribution to optimizing entrepreneurial performance. The method used is a Systematic Literature Review (SLR), which examines various relevant scientific publications and then categorizes the findings to obtain a comprehensive overview of effective strategies for improving managerial competency. The results indicate that technical skills, human relations skills, and conceptual skills play a significant role in supporting decision-making processes, resource management, and adapting business strategies to business dynamics. The findings also indicate that training, mentoring, continuous learning, and the use of technology are development strategies capable of significantly increasing productivity and efficiency. The implications of this research emphasize that improving managerial skills is a strategic necessity for entrepreneurs to strengthen competitiveness, increase operational effectiveness, and promote business sustainability. Furthermore, this research provides a basis for the development of more structured training programs and supporting policies to strengthen the managerial capacity of entrepreneurs.

This study analyzes the maintenance process of the Roll Bending machine used in the wind tower production line at PT Kenertec Power System, Cilegon, Indonesia. The Roll Bending machine plays a crucial role in shaping steel plates into cylindrical shell components, which are later assembled into wind tower sections. The objective of this research is to identify maintenance patterns, types of failures, and improvement strategies to ensure machine reliability and operational efficiency. The research employed observation, interviews with maintenance personnel, and documentation review to collect relevant data. The findings show that the machine experienced multiple failures, mostly related to hydraulic system leaks, PLC programming errors, and component wear such as cylinders, seals, and gear pumps. A significant increase in corrective maintenance activities occurred between August 2023 and April 2024, particularly in February 2024, indicating the need for a more consistent predictive maintenance strategy. The implications of this study highlight that optimized maintenance scheduling and monitoring are essential to reduce downtime, avoid production delays, and maintain product quality. This research is expected to support maintenance decision-making and contribute to the improvement of industrial machine reliability in wind tower manufacturing operations.

This study explores the impact of Artificial Intelligence (AI) integration and algorithm transparency on organizational efficiency and perceived fairness in Human Resource (HR) decision-making. Using a qualitative literature review approach, the research examines the mediating role of employee trust and the moderating influence of organizational culture. The analysis focuses on peer-reviewed international studies published since 2020, reflecting the latest theoretical and empirical developments in AI and HR management. The findings reveal that a higher level of AI integration improves decision speed, reduces operational costs, and increases the accuracy of talent allocation. However, these efficiency gains are not independent of ethical considerations. Transparent algorithms are shown to significantly enhance employees’ trust and perceptions of fairness, whereas opaque systems tend to generate resistance and distrust. Furthermore, organizational culture plays a crucial moderating role. Companies with innovative and participatory cultures report better outcomes from AI implementation, while hierarchical cultures are associated with lower adoption success and ethical challenges. This research highlights the importance of aligning technical capabilities with social and cultural factors to optimize the use of AI in HR functions. The study contributes to the discourse on socio-technical systems by proposing an integrative framework that links AI integration, transparency, trust, and culture to key organizational outcomes. Practical implications include the need for transparent system design, ethical governance, and cultural readiness to support responsible AI adoption in HR.

Global trade has long been promoted as a driver of economic growth and international cooperation. The World Trade Organization (WTO), established to ensure fairness and stability in global trade, plays a central role in shaping trade relations among nations. However, concerns persist regarding its impact on developing countries. This study aims to examine how WTO policies influence economic inequality and structural dependency in developing economies. Using a qualitative research approach, this article integrates legal and economic perspectives to analyze relevant literature and assess the WTO's institutional mechanisms. The findings reveal that, although the WTO seeks to promote equitable trade, its policies tend to favor developed countries through liberalization and intellectual property regimes that restrict policy flexibility in developing nations. These mechanisms reinforce technological dependency, reduce competitiveness, and perpetuate unequal participation in global markets. The study concludes that without institutional reform, the WTO framework will continue to sustain global trade imbalances. This article proposes alternative solutions, including enhancing regional and South–South trade cooperation, promoting fair technology transfer, and reforming the WTO's decision-making structures. These measures could foster a more inclusive and balanced trading system that supports sustainable development in the Global South.

Digital transformation in the field of information technology requires Micro, Small, and Medium Enterprises (MSMEs) to improve the quality of financial management to be able to compete sustainably. One effort that can be done is through the implementation of the Financial Management Information System (MISK). This study aims to analyze the implementation of MISK in MSMEs, examine the benefits obtained, and identify obstacles faced in the implementation process. The research method used is a qualitative descriptive approach with data collection techniques through interviews, observation, and documentation. The object of the study is the culinary MSME "Dapur Lestari Jambi" which has implemented a digital financial recording application and Point of Sale (POS) system. The results of the study indicate that the implementation of MISK can increase the accuracy of transaction recording, accelerate the preparation of financial reports, improve cash flow management, and support data-based managerial decision-making. However, the implementation of MISK still faces several obstacles, especially related to limited human resource competency, consistency of recording, and adaptation to technology. This study concludes that the Financial Management Information System has a strategic role in increasing the efficiency, transparency, and professionalism of MSME financial management, and is an important factor in supporting business sustainability in the digital era.  

This comparative study analyzes the models of character education by comparing the implementation of Social and Emotional Learning (SEL) in Finland and the Akhlak (Moral) Curriculum within Islamic Religious Education (PAI) in Indonesia. Modern education demands not only cognitive intelligence but also emotional and moral maturity, highlighted by rising issues like bullying and mental health problems in adolescents. Finland's success is attributed to the strong integration of SEL, a psychological method focusing on five core competencies (self-awareness, self-management, social awareness, relationship skills, and responsible decision-making) that fosters a positive school climate. In contrast, Indonesia's PAI Akhlak Curriculum aims to form character rooted in theological-spiritual values (piety and obedience). Using a descriptive qualitative comparative method through literature review and content analysis, the study found that despite sharing the core objective of cultivating moral character , their foundations differ: SEL is secular-humanistic for well-being, while Akhlak is theological-spiritual. Furthermore, Finland's system employs a low-pressure, integrated, formative evaluation, supported by teacher autonomy, while Indonesia's PAI implementation faces challenges from a dominant focus on quantitative cognitive assessment. The study recommends that PAI adopt the structured SEL framework as a methodological bridge to translate Akhlak values into concrete student behavior and promote active, affect-focused learning.

Early childhood development assessment is an important process in obtaining a comprehensive picture of a child's growth and development as a basis for planning learning that is appropriate to the child's needs and characteristics. One of the most relevant assessment techniques for early childhood characteristics is observation, because it is carried out naturally through play and learning activities without putting pressure on the child. This article aims to examine the use of observation instruments as a basis for assessing early childhood development and to provide guidance to early childhood educators in conducting appropriate, systematic, and accountable assessments. The method used in this article is a theoretical study that examines the concept of early childhood assessment, assessment principles, and the process of conducting assessments through observation. The observation instruments discussed include daily records, anecdotal records, and children's work records. The results of the study show that the optimal use of observation instruments can help teachers understand children's development holistically, detect children's special needs, and serve as a basis for decision-making in learning planning and curriculum development. Thus, observation instruments play a strategic role in supporting the assessment process of early childhood development to be more meaningful and oriented towards children's needs.

This study investigates the role of knowledge management (KM) capabilities in enhancing managerial decision-making within organizational settings. Using a systematic review approach, ten peer-reviewed journals published between 2019 and 2024 were analyzed to identify key themes, patterns, and empirical findings related to knowledge management implementation and its influence on decision-making processes. The review reveals that strong knowledge management capabilities particularly in knowledge acquisition, storage, sharing, and utilization significantly contribute to improving the accuracy, speed, and strategic quality of managerial decisions. The findings also show that organizations with well-developed knowledge management infrastructures, supported by digital technologies and a culture of knowledge sharing, demonstrate greater adaptability, innovation, and problem-solving effectiveness. This study concludes that knowledge management capabilities are essential for strengthening evidence-based decision-making and enhancing organizational competitiveness. Implications for managers emphasize the need to invest in knowledge management systems and foster collaborative knowledge practices. Suggestions for future research include expanding the scope to cross-industry comparisons and integrating knowledge management with emerging technologies such as AI-based decision support systems..