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This study aims to analyze the implementation of the Balanced Scorecard (BSC) as a strategic performance evaluation tool in the era of digital transformation. Using a descriptive qualitative approach within the social constructivist paradigm, data were collected through in-depth interviews, non-participant observation, and document analysis in three organizations undergoing digitalization. Thematic analysis (Braun & Clarke, 2006) identified four main themes in the application of the BSC: digital strategy alignment, digital readiness and data integration, a culture of learning and innovation, and adaptive leadership transformation. The findings indicate that the BSC functions not only as a performance measurement system but also as an adaptive, collaborative, and data-driven strategic management framework. The integration of digital technologies accelerates decision-making processes and strengthens reflective organizational culture. Theoretically, this study extends the classical BSC model of Kaplan and Norton (1996, 2001) toward a Digital Balanced Scorecard that emphasizes synergy among strategy, data, and organizational learning. Practically, the results highlight the importance of digital readiness, an innovation-oriented culture, and adaptive leadership as key foundations for successful BSC implementation in the era of digital disruption.

The professional competence of Islamic Education (PAI) teachers plays a decisive role in determining the quality of learning at the elementary school level. In practice, many teachers still encounter challenges in mastering subject content, developing systematic teaching materials, applying innovative learning strategies, and integrating educational technology into classroom activities. These conditions indicate the need for structured professional development efforts through collaborative forums. This study aims to analyze the role of the Islamic Education Teachers Working Group (KKG PAI) in maximizing the professional competence of PAI teachers in public elementary schools in Panti District, Pasaman Regency, and to identify the supporting and inhibiting factors influencing its implementation. This research employed a qualitative approach with a case study design. Data were collected through in-depth interviews, participatory observation, and documentation involving the KKG supervisor, the head of KKG PAI, and member teachers. Data analysis was conducted using an interactive model consisting of data reduction, data display, and conclusion drawing. The findings reveal that KKG PAI functions as a strategic platform for collaborative lesson planning, subject-matter enrichment, peer reflection, and technology-based instructional training. Supporting factors include strong teacher commitment and collaborative culture, while limitations in facilities and technological disparities remain challenges. Strengthening the sustainability and management of KKG programs is essential to enhance teachers’ professional competence and improve the overall quality of Islamic education learning.

Public health is a crucial aspect of improving well-being, particularly at the village level. However, in Srigading Village, Lawang District, Malang Regency, access to information related to health services remains a significant challenge, resulting in suboptimal utilization of Posyandu and Puskesmas services. To address this issue, a web application called “Srigading Sehat” has been developed as a digital platform providing health service information through interactive maps and service schedules. This community service activity employs the IDEA approach (Identify Objective, Design Action Steps, Engage Our Plan, Assess and Follow Up) as a systematic framework. The Identify Objective stage identified limitations in health information access; Design Action Steps designed a participatory learning-based application development model; Engage Our Plan implemented application development, socialization, and training for 25 participants comprising village officials, posyandu cadres, and the general community; and Assess and Follow Up evaluated achievements through Firebase Analytics monitoring. Results showed increased health information access marked by 500 health information page visits within the first 30 days of launch, with total Firebase reads reaching 631 (+1,026.8%). Four village health facilities are actively registered and using the application to independently update their service information. This application is anticipated to serve as an appropriate technological innovation contributing to the enhancement of health services at the village level.

This study investigates the influence of financial literacy, entrepreneurship training, and financial inclusion on the performance of micro, small, and medium enterprises (MSMEs) through business sustainability. Using a systematic literature review (SLR) examines the impact of financial literacy, entrepreneurship training, and financial inclusion on MSME performance through business sustainability mediation by synthesizing empirical data from 12 research (2020–2025) across Scopus and Web of Science. Positive direct effects on sustainability (financial literacy via budgeting/risk management; training via adaptive resilience; inclusiveness via digital access) and performance metrics like profitability/growth are confirmed by results using the PRISMA 2020 flow.  Amid obstacles like financial access restrictions and COVID-19 disruptions, business sustainability appears as a crucial mediator, linking these factors to improved MSME results in developing contexts (Africa, Indonesia). Practical implications compel policymakers to give integrated literacy programs, contextual training, and inclusive finance top priority. Theoretical contributions combine financial literacy, entrepreneurial learning, and sustainability ideas into a holistic mediation model. The results highlight the importance of integrating financial education, entrepreneurial skill development, and inclusive financial systems to strengthen MSME resilience and competitiveness. This study provides practical implications for policymakers, financial institutions, and support organisations in designing effective interventions that foster sustainable business growth. The research also contributes theoretically by confirming the mediating role of business sustainability in the relationship between financial literacy, entrepreneurship training, financial inclusion, and MSME performance. Future studies may expand these insights by examining additional contextual factors such as digital technology adoption and business networking that further support sustainable MSME development.

This study aims to analyze the internal and external conditions of Karel Workshop in Wairhubing, Sikka Regency, using a SWOT approach (Strengths, Weaknesses, Opportunities, and Threats) as a basis for formulating business development strategies. The research employed a qualitative descriptive method with data collected through in-depth interviews with the owner, employees, and customers, as well as secondary data from documents and official statistics. The findings indicate that Karel Workshop possesses several strengths, including meticulous service quality, strong interpersonal relationships with customers, and mechanic skills acquired through self-learning. However, the workshop also faces weaknesses such as limited equipment, the absence of a structured management system, and a lack of digital promotion. Opportunities that can be utilized include high public interest in motorcycle modification, potential motorcycle painting services, a strategic location, and possible partnerships with spare-part suppliers. Meanwhile, the main threats include rising spare-part prices, competition among workshops, and occupational safety risks. Overall, the study recommends strengthening digital promotion, improving business management, enhancing workshop facilities, and implementing safety standards to support the sustainable development of Karel Workshop. 

This study aims to analyze the internal and external conditions of Karel Workshop in Wairhubing, Sikka Regency, using a SWOT approach (Strengths, Weaknesses, Opportunities, and Threats) as a basis for formulating business development strategies. The research employed a qualitative descriptive method with data collected through in-depth interviews with the owner, employees, and customers, as well as secondary data from documents and official statistics. The findings indicate that Karel Workshop possesses several strengths, including meticulous service quality, strong interpersonal relationships with customers, and mechanic skills acquired through self-learning. However, the workshop also faces weaknesses such as limited equipment, the absence of a structured management system, and a lack of digital promotion. Opportunities that can be utilized include high public interest in motorcycle modification, potential motorcycle painting services, a strategic location, and possible partnerships with spare-part suppliers. Meanwhile, the main threats include rising spare-part prices, competition among workshops, and occupational safety risks. Overall, the study recommends strengthening digital promotion, improving business management, enhancing workshop facilities, and implementing safety standards to support the sustainable development of Karel Workshop. 

Primary Healthcare Facilities (Fasilitas Kesehatan Tingkat Pertama, FKTP) represent the first level of contact in the healthcare system and play a central role in infection prevention and control. Despite mandatory Infection Prevention and Control (IPC) training in Indonesia, evidence regarding its effectiveness in improving cognitive abilities among primary healthcare workers remains limited. This study aimed to evaluate the effectiveness of IPC training in enhancing the cognitive abilities of healthcare workers in FKTP. A quasi-experimental study with a one-group pretest–posttest design was conducted involving 91 healthcare workers who participated in IPC training across three cohorts in 2024. The training was delivered online through a Learning Management System and consisted of structured learning modules accompanied by a pre-test and a final quiz. Cognitive improvement was assessed using paired samples t-tests, while the magnitude of training impact was evaluated using Cohen’s dz effect size. The results showed statistically significant improvements in cognitive scores across all cohorts (p < 0.001), with mean score increases ranging from 16.10 to 23.35 points. Effect size analysis revealed large to very large effects, with an overall Cohen’s dz of 1.19, indicating substantial and practically meaningful cognitive gains. In conclusion, IPC training was effective in improving cognitive competence among FKTP healthcare workers. These results reinforce the value of well-structured training programs as an essential component of efforts to strengthen infection prevention capacity in primary healthcare settings.

Student dropout remains a significant challenge for higher education institutions as it impacts academic quality, educational management efficiency, and students' success in completing their studies. Therefore, an approach that can identify students at risk of dropping out is necessary so that timely academic interventions can be made. This study aims to develop a dropout detection model using an Artificial Neural Network (ANN). The data used come from a publicly available higher education dataset, ensuring research reproducibility. Data preprocessing steps were carried out to improve data quality before modeling, and the Synthetic Minority Over-Sampling Technique combined with Edited Nearest Neighbors (SMOTE-ENN) was applied to address class imbalance issues. The ANN model's performance was evaluated using accuracy, precision, recall, F1-score, and area under the ROC curve (ROC-AUC). The test results show that the ANN model can provide excellent predictive performance in detecting at-risk students. The application of SMOTE-ENN also proved to enhance the model’s sensitivity toward the minority class, as indicated by improvements in recall and F1-score. These findings indicate that the developed ANN model has the potential to be used as a student dropout detection system to support data-driven decision-making and strategy development within higher education institutions.

Digital transformation has significantly reshaped human resource management (HRM) through the adoption of Human Resource Information Systems (HRIS), artificial intelligence (AI), big data analytics, e-learning platforms, and remote work technologies. Although these innovations improve efficiency and decision-making, they also generate ethical challenges related to data privacy, algorithmic bias, transparency, and employee monitoring. This article examines the role of professional ethics in HRM within the context of digital transformation, highlighting both emerging challenges and potential opportunities. This study employs a conceptual research approach supported by a comprehensive literature review of scholarly works on HRM, professional ethics, and digitalization. The analysis focuses on core ethical principles such as integrity, fairness, responsibility, professionalism, and confidentiality, and evaluates their implementation in digital HR practices. The findings indicate that unethical use of digital technologies may lead to discrimination, reduced employee trust, and violations of individual rights, particularly through biased AI-based recruitment systems and opaque performance evaluation mechanisms. However, digital transformation also offers opportunities to strengthen ethical HR governance. The use of ethical data management, algorithmic audits, digital transparency, and e-learning-based ethics training can enhance accountability and fairness in HR processes. The study concludes that integrating professional ethics with digital HRM is essential for developing human-centered, sustainable, and trustworthy organizations in the digital era.

The rapid development of digital streaming platforms such as Netflix has generated a large volume of content data with diverse characteristics, thereby requiring effective analytical methods to understand emerging patterns and trends. This study aims to classify Netflix content into two main categories, namely movies and television shows, and to analyze genre trends and content characteristics using a data mining approach with the Naive Bayes algorithm. The dataset used in this study is the Netflix Shows dataset, consisting of 8,809 content entries, with the primary features analyzed including genre, rating, and country of production. The research process begins with data exploration and preprocessing stages, including data cleaning, handling missing values, and transforming categorical features to enable effective model construction. Subsequently, the dataset is divided into training and testing sets to objectively and systematically build and evaluate the Naive Bayes classification model. Model performance is evaluated using accuracy, precision, recall, and F1-score metrics to assess the model’s ability to accurately distinguish between Netflix content types. The experimental results demonstrate that the Naive Bayes algorithm is able to classify Netflix content into Movie and TV Show categories with accuracy, precision, recall, and F1-score values of 100%, respectively. The confusion matrix indicates that no misclassification occurred, suggesting that genre, rating, and country of production features provide a very clear separation between content classes. These findings indicate that the Naive Bayes algorithm can achieve exceptionally high classification performance with optimal evaluation results. The results further reveal distinct differences in characteristics between movies and television shows based on genre and production attributes. Therefore, this study is expected to contribute to the development of content recommendation systems and strategic content management within the streaming industry.

Tourism is one of the sectors that plays an important role in boosting economic growth through travel activities and destination exploration. Tourists' preferences for nature-based tourism options, such as mountain hiking or beach tourism, are influenced by various factors, ranging from personal experiences and recreational interests to social characteristics. Therefore, a technology-based approach is needed to predict destination choice tendencies more accurately. As artificial intelligence technology develops, deep learning methods have been widely used in classification processes due to their ability to process large amounts of data and recognize complex patterns. In this study, a Multilayer Perceptron (MLP) model is used to classify tourists' preferences between mountain or beach destinations based on a survey dataset. The research stages include data processing, data splitting using a train-test split, model training, and performance evaluation using accuracy, precision, recall, and F1-score. The test results show that the MLP model is capable of achieving an accuracy rate of 99%, confirming that deep learning methods are effective in automatically mapping tourism preference trends. This research is expected to serve as a basis for the development of more personalized travel destination recommendation systems, as well as to support tourism management in formulating targeted promotional strategies.

Artificial intelligence (AI) is currently a rapidly developing technology in all fields, particularly in finance and the military. This study aims to examine the application of Artificial Intelligence (AI) technology to support financial report analysis and internal control within Indonesian Navy (TNI AL) work units. Along with the development of information technology, AI has the potential to provide innovative solutions to improve efficiency, accuracy, and transparency in state financial management, particularly in a military environment that demands high accountability. The research method used was descriptive qualitative with a case study approach in several work units within the Indonesian Navy. Data were obtained through interviews, observations, and a review of relevant documents and literature. The results indicate that the use of AI, such as machine learning and data analytics, can identify unusual financial transaction patterns, predict potential irregularities, and improve the effectiveness of internal oversight. However, the implementation of this technology still faces challenges, such as limited digital infrastructure, the need for human resource training, and the need for policies that support sustainable digital transformation. This study recommends the gradual and strategic integration of AI as part of the reform of the Indonesian Navy's financial management system.

Early Childhood Education (PAUD) holds a very important role in shaping children’s character, moral values, and foundational knowledge. As an effort to support the success of education, good quality learning outcomes are required as a benchmark for children’s holistic development. In this context, educator management becomes one of the keys to improving the quality of learning outcomes. PAUD Al-Qur’an (PAUDQU) is an early childhood education institution that prioritizes Al-Qur’an education and Al-Qur’an memorization (tahfidz) as its institutional uniqueness. The findings of this research show that the educator management implemented in PAUDQU in Setu Bekasi District is quite good, as almost all elements within the scope of educator management have been carried out by the school. However, there are several obstacles found in its implementation, such as the educators’ competencies that have not been maximized, particularly in Al-Qur’an recitation (tahsin) and tahfidz, as well as the promotion, compensation, and educator assessment systems that are not yet well-structured. KIPAS EVA, an acronym for Competence Implementation Evaluation Appreciation, was developed with the expectation of being easier to remember, thus supporting the process of applying educator management in the future. This management strategy emphasizes educator planning by strengthening competencies, professional learning implementation by educators, continuous educator evaluation, and providing appreciation to increase educator motivation.

Waste has become a serious environmental problem in Indonesia, which continues to increase along with population growth. The issue of waste management poses serious challenges for the environment, especially in the process of separating organic and inorganic waste. In the field of computer vision, recognising the type and shape of waste through camera images remains a challenge due to variations in shape, colour, and complex lighting conditions. Therefore, this problem utilises Deep Learning technology, which is expected to be widely applied in Indonesia, especially in large cities with high waste volumes. This study aims to distinguish between organic and inorganic waste using the Convolutional Neural Network (CNN) method based on digital images. The developed CNN model was trained to recognise the visual patterns of each type of waste and tested to measure its accuracy. The test results show that the CNN-based classification system is capable of achieving an accuracy rate of 95%, thus proving the effectiveness of this method in supporting artificial intelligence-based automatic waste sorting systems.

The quality of education is a crucial issue that continues to receive attention in facing the challenges of globalization, digitalization, and the demands of 21st century competencies. Quality improvement efforts are not only related to the quality of students' learning outcomes, but also concern the role of leadership, management effectiveness, and the implementation of a quality assurance system. This study aims to identify strategies to improve the quality of education that have been studied in the literature for the last five years (2020-2025) and answer two research questions, namely: (1) what quality strategies are predominantly discussed in the literature, and (2) how the role of leadership, strategy management, and quality assurance in supporting the quality of education. The method used is literature review with a qualitative approach. Data was obtained from Google Scholar and Publish or Perish (PoP) databases using the keyword "quality strategy" with a publication year limit of 2020–2025. The search yielded 30 articles, which then through a screening and selection process obtained 5 relevant articles for analysis. The results of the analysis show three main trends: (1) the strategic role of school principals in building a quality culture, (2) the importance of evaluation and implementation of quality management in a sustainable manner, and (3) the synergy of visionary leadership with the quality assurance system  as the basis for sustainable quality. This study concludes that the education quality strategy requires the integration of these three aspects. Going forward, further research is needed to develop integrative models across approaches and broader educational contexts.

The persistent issue of high youth unemployment among Senior High School (SHS) graduates necessitates cultivating an entrepreneurial mindset through formal education, making Entrepreneurship Education (EE) a national strategic imperative. This Systematic Literature Review (SLR) critically analyzed 15 empirical articles, selected via the strict PRISMA protocol, to evaluate the effectiveness of diverse EE curriculum models in enhancing students' Entrepreneurial Interest (Intention) and Attitude. The key finding is that EE implementation is substantially effective only when executed through active, experience-based pedagogical models such as Experiential Learning, Project-Based Learning (PjBL), and the Teaching Factory which are superior in fostering practical competency and significantly boosting Entrepreneurial Self-Efficacy and positive Attitude, consistent with the Theory of Planned Behavior. Successful implementation also critically depends on robust operational factors, including structured curriculum management (e.g., PDCA cycle) and the availability of competent teachers. In conclusion, the findings provide a strong evidence-based framework, recommending that policymakers prioritize experiential models and integrate modern elements like Digital Literacy and Non-cognitive Skills to produce SHS graduates with genuine entrepreneurial readiness.

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.

The digital era demands that organizations be fast-moving, adaptable, and innovative. With the advancement of information technology, changes in work methods, global competition, and stakeholder demands are becoming increasingly complex. Knowledge Management (KM) plays an important role as a strategic mechanism for identifying, acquiring, storing, sharing, and utilizing knowledge to improve organizational effectiveness and efficiency. In this context, knowledge management becomes one of the important elements for organizations to enhance performance. Knowledge management is not just about collecting data or information, but how organizations can store, share, create, and utilize knowledge to gain a competitive advantage. This article aims to analyze the importance of knowledge management for organizational performance in the digital age, including how the digital era changes the dimensions of knowledge management, how knowledge management contributes to organizational performance, the challenges faced, and their implications. The data obtained for this study were gathered from observations thru interviews with relevant parties and a literature review study by examining the results of empirical research from the past five years (2020–2025). The method used was descriptive literature analysis of 15 scientific articles from accredited national journals. The analysis focuses on the relationship between knowledge management dimensions (knowledge creation, storage, sharing, and application) and organizational performance indicators (financial performance, innovation, productivity, and customer satisfaction). The study results show that the implementation of knowledge management significantly contributes to improving organizational performance, both directly thru increased efficiency and effectiveness of work processes, and indirectly thru strengthening a culture of innovation and organizational learning. This article asserts that an organization's success in the digital age is not solely determined by its ability to adopt technology, but also by its ability to manage and leverage knowledge as a strategic resource. Therefore, knowledge management needs to be systematically integrated into the organization's digital strategy, accompanied by strengthening a learning culture, human resource training, and adaptive information technology systems.

Innovation is the process of optimizing various resources to produce more efficient and sustainable solutions. This study aims to examine the relationship between resources and innovation strategies in supporting sustainable entrepreneurship through a Systematic Literature Review (SLR) approach. A total of 25 scientific articles were analyzed using PRISMA guidelines to examine the role of resources such as human, technological, information, financial, and physical resources in the context of product, process, and managerial innovation. The research findings indicate that the success of innovation is strongly influenced by the organization's ability to utilize and synergize its resources, especially in the development of internal capabilities such as tacit knowledge, research and development activities, and digital technology. Human resource creativity is the main driver of product innovation, while process innovation is strengthened by the application of technology and a learning culture. Managerial innovation is heavily influenced by entrepreneurial orientation and dynamic capabilities in responding to change. The implementation of sustainable innovation strategies such as green, digital, and social innovations also increases business competitiveness through cross-sector collaboration. This study emphasizes the importance of integrated resource management and innovative strategies to achieve sustainability, especially in the small and medium enterprise sector.

Education is a fundamental right that must be fought for by every child in the nation, and throughout its development, it continues to undergo innovations and evaluations toward better quality. One educational model that is growing in Indonesia is the boarding school system, which has its own characteristics, advantages, and challenges. This study aims to describe the social studies (IPS) teachers’ strategies in boarding school–based learning, the implementation of IPS learning within the boarding school environment, and the obstacles faced by IPS teachers at MTs Darul Hikmah. This research employs a qualitative approach with a case study design. The study was conducted at Pondok Modern Darul Hikmah Tulungagung, with seventh-grade students as research subjects. Data collection techniques included observation, interviews, and documentation. The results show several factors that influence the low effectiveness of IPS learning in boarding schools, including the dense institutional activity schedule that reduces students’ learning focus, teachers’ limited mastery of the subject matter and classroom management, and the dual curriculum implemented simultaneously within the institution. Efforts to improve IPS learning effectiveness include enhancing teacher discipline when entering and leaving the classroom, utilizing audio-visual learning media, and connecting learning materials with current issues to make the lessons more relevant and engaging. Furthermore, the study reveals several advantages of boarding school–based education, such as fostering students’ independence, developing social awareness, providing deeper religious instruction, and integrating both general and religious education. Thus, IPS learning in boarding schools has the potential to develop more optimally with the support of appropriate learning strategies and more structured institutional management.