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This study examines the regulation of copyright royalties as joint property in Indonesia, the United States, and Europe, aiming to provide recommendations for better legal implementation. The research employs a normative juridical method with a comparative legal approach, utilizing library research and qualitative analysis of primary and secondary legal materials. The findings indicate that Indonesia, the United States, and Europe share common ground in recognizing royalties derived from copyright as joint property when such economic benefits are obtained during marriage. However, significant differences exist in their approaches. European countries, particularly Spain and the Republic of Moldova, clearly distinguish between exclusive rights and economic rights, where copyright remains the creator's personal property while royalties are classified as joint property. The United States demonstrates considerable flexibility through state-level regulations, adopting either community property systems or equitable distribution systems. Indonesia, through Decision No. 1622/PDT.G/2023/PA.JB, has begun recognizing royalties as joint property. Nevertheless, Indonesia still requires clearer and more comprehensive regulations to ensure legal certainty regarding the status of royalties as joint property and their distribution following divorce. This study contributes to developing legal frameworks that balance protecting creators' personal rights with the principle of fairness in family law.

This study aims to analyze the paradox of stunting in Yemen, particularly the disconnect between humanitarian response priorities and children's actual nutritional needs amid the ongoing conflict. Stunting, a form of chronic malnutrition, is a significant public health issue in Yemen, exacerbated by the conflict's disruption of food, healthcare, and sanitation systems. Despite the clear evidence of rising stunting rates, international humanitarian interventions tend to focus on addressing acute crises, such as extreme hunger, while neglecting long-term nutritional needs. Using a qualitative literature review approach, the research synthesizes data from archival documents, reports, and secondary sources to explore the structural causes of stunting and the challenges faced by humanitarian actors in Yemen. The findings reveal that the protracted conflict, economic collapse, and humanitarian blockades have worsened food insecurity and malnutrition. Moreover, the humanitarian response often prioritizes short-term survival over long-term prevention of stunting, resulting in a lack of integrated, multisectoral interventions. The study emphasizes the need for a paradigm shift in humanitarian policies to incorporate long-term development strategies and integrate stunting prevention. This research contributes to the academic understanding of the humanitarian-development nexus and offers recommendations for more holistic interventions.

This research is motivated by the problems in manual attendance systems at schools, which remain vulnerable to fraud, time-consuming, and inefficient. The expected solution is to develop an automated attendance system based on face recognition that can operate in realtime with high accuracy. The research object is vocational high school students, with the applied method implementing the YOLO v10 algorithm for face detection, followed by the face_recognition library for identification. The instruments used include an Imou CCTV camera as the input device, a mid-range laptop as the hardware platform, and Python with SQLite as the software environment for data processing and attendance storage. The results show that the developed system achieved an average face detection accuracy of 96% under normal lighting and 91% under low lighting, with an average processing speed of 27 FPS. The implementation of an anti-duplication feature also ensured data validity by allowing each student to be recorded only once per day. In conclusion, the use of YOLO v10 in face-based attendance proved to be effective, efficient, and capable of reducing fraud. The implication of this study is that the system can be applied in both Islamic boarding schools and general schools as a modernization of attendance systems, with a recommendation for further development through web-based application and cloud database integration.

Data security in Electronic Medical Records (EMR) is a crucial issue in health information governance in Indonesia. This study evaluates the compliance of health facility information security systems with Ministry of Health Regulation (PERMENKES) No. 24 of 2022 and Personal Data Protection Law (UU PDP) No. 27 of 2022, and analyzes the impact of non-compliance on service quality and patient trust. The method employed is a systematic narrative literature review on the Google Scholar database (2023–2026) using the keywords "data security and privacy," "electronic medical records," and "CIA Triad," focusing on the implementation of Confidentiality, Integrity, and Availability. The four healthcare facilities examined have implemented controls such as role-based access control, Electronic Signatures (TTE), Virtual Private Networks (VPN), data encryption, and SSL/TLS protocols in accordance with PERMENKES provisions and Article 35 of the UU PDP. However, the effectiveness of implementation is hindered by weak authentication due to the use of simple passwords and excessively long auto-logout durations, the absence of comprehensive written standard operating procedures (SOPs), low staff compliance with security protocols, and minimal patient awareness regarding personal data protection rights. These weaknesses heighten the risk of patient data breaches as well as potential administrative sanctions and fines, and carry negative implications for service quality and public trust. Recommendations include strengthening internal security policies, developing written SOPs, providing continuous training for healthcare workers, implementing stronger authentication mechanisms (e.g., multi-factor authentication/MFA), and conducting patient awareness programs to ensure regulatory compliance and maintain public confidence.

This study aims to formulate an information system strategic planning model for PT Athria Cipta Mandiri using the Ward and Peppard method. The research was conducted because the company still faces several problems in managing tender and construction project data, such as unintegrated systems between divisions, semi-digital administrative processes, repeated data input, the absence of a centralized database, and project reporting that has not been carried out in real time. This study uses a qualitative descriptive approach with data collection techniques through observation, interviews, and literature study. The analysis was conducted using Value Chain, PESTEL, SWOT, Critical Success Factor, McFarlan Strategic Grid, and application portfolio recommendations. The results show that PT Athria Cipta Mandiri needs an integrated information system for tender and project management, web-based project reporting and monitoring, a document management system, business intelligence dashboard, centralized cloud database, and stronger IT governance. The proposed strategy is expected to improve operational efficiency, data accuracy, inter-division coordination, and data-based managerial decision making.

Soybean is an important food commodity in Indonesia because it is the main raw material for tofu and tempeh, two major protein sources widely consumed by the population. However, domestic soybean production remains far below national demand resulting in heavy dependence on imports. In contrast maize is increasingly preferred by farmers due to its higher productivity and a more stable economic value. Therefore, maize–soybean intercropping has emerged as a promising strategy to improve land-use efficiency while increasing soybean production without reducing maize cultivation. This study systematically mapped and synthesized maize–soybean intercropping research in Indonesia and conducted a meta-analysis of Land Equivalent Ratio LER values reported across studies. Literature searches using Scopus, Web of Science, and Google Scholar identified 179 eligible publications published between 1978 and 2023. Most studies focused on agronomic factors such as variety selection spacing arrangement and fertilizer management. Meta-analysis showed average LER values of 1.47 ± 0.046 for maize–soybean intercropping and 1.36 ± 0.081 for maize–mung bean intercropping indicating advantages over monoculture systems. However, inconsistencies in methodology and reporting standards limited study comparability and sustainability assessments. Future research should integrate ecological, social, and long-term economic indicators alongside standardized reporting frameworks to strengthen evidence-based intercropping recommendations nationally for sustainable agriculture.

This study aims to analyze natural resource management strategies within the framework of sustainable development administration in Indonesia. Using a qualitative approach and policy analysis methods, the research evaluates existing regulations, institutional capacities, and the effectiveness of policy implementation in ensuring resource sustainability. The study examines a range of policy instruments, from sectoral regulations and decentralization mechanisms to community-based programs. Findings reveal that regulatory fragmentation, weak inter-agency coordination, limited local government capacity, and suboptimal governance practices constitute the primary challenges to sustainable natural resource management. The research affirms that an integrated and collaborative approach encompassing ecological, economic, and socio-cultural dimensions is a prerequisite for achieving sustainable development. Policy recommendations include regulatory reform, institutional strengthening, indigenous community empowerment, development of integrated monitoring systems, and mainstreaming sustainability principles throughout the national and regional development planning cycles.

This study examines disaster management strategies in earthquake-prone countries, with a comparative focus on Japan and the Philippines as case studies for lessons applicable to public administration systems worldwide. Using a qualitative comparative analysis approach, the research evaluates institutional frameworks, policy instruments, community engagement mechanisms, and intergovernmental coordination systems deployed in both countries. Japan’s highly centralized yet locally adaptive Disaster Management Basic Act framework is contrasted with the Philippines’ decentralized National Disaster Risk Reduction and Management (NDRRM) system. Findings reveal that effective disaster management hinges on five critical pillars: strong legal frameworks, inter-agency coordination, investment in early warning systems, community resilience programs, and post-disaster recovery governance. The study further identifies that public trust, administrative capacity, and fiscal decentralization significantly influence disaster response outcomes. Lessons drawn from both countries offer practical recommendations for developing nations seeking to strengthen their disaster governance architectures. This research contributes to the growing body of knowledge on comparative public administration and disaster risk reduction, underscoring the imperative of integrated, adaptive, and community-centered governance frameworks in seismically active regions.

The increasing role of information technology in higher education requires IT governance practices that are measurable, structured, and aligned with digital transformation objectives. Many higher education institutions have implemented various information systems to support academic, administrative, and managerial services; however, the existence of technology does not automatically ensure that IT processes are governed effectively. This study aims to evaluate the Capability level of IT governance using the COBIT 2019 framework in the context of a state university in Indonesia. A descriptive case study approach was applied through structured interviews, document analysis, and observation of IT governance practices. The evaluation focused on eleven Governance and Management Objectives across the EDM, APO, BAI, DSS, and MEA domains. The results show that most objectives are at Capability Level 1 (Performed), while only BAI01, BAI03, and DSS02 have reached Capability Level 2 (Managed). No evaluated objective has reached Level 3 (Established). The gap analysis indicates that the highest gaps are found in EDM03, APO12, and APO13, which relate to risk optimization, risk management, and security governance. These findings indicate that IT governance practices have been implemented but still require stronger formal policies, standardized procedures, documented controls, and integrated monitoring mechanisms. The study provides practical recommendations for improving IT governance through risk appetite definition, risk register development, information security policy, enterprise architecture blueprint, service level agreement implementation, and performance monitoring to support sustainable digital transformation in higher education.

Mental health issues among university students have become a growing concern, driven by academic pressures, career uncertainties, and complex social transitions. However, a large proportion of students remains reluctant to seek professional psychological support due to social stigma and limited access to institutional counseling services. This study proposes the design and implementation of an Android-based chatbot application that integrates mood tracking and sentiment analysis to continuously monitor the emotional states of university students. The system employs a fine-tuned RoBERTa (Robustly Optimized BERT Pretraining Approach) model trained on the EmoContext conversational dataset (SemEval-2019 Task 3), comprising 30,160 labeled three-turn dialogue instances across four emotion classes: angry, happy, sad, and others. The model was fine-tuned for four epochs using the AdamW optimizer with a learning rate of 2e-5 and a maximum sequence length of 128 tokens. Evaluation on a held-out validation set of 6,032 samples yielded an overall accuracy of 88.28%, a macro-average F1-score of 0.87, and a weighted-average F1-score of 0.88. Per-class F1-scores were 0.89 (angry), 0.83 (happy), 0.91 (others), and 0.86 (sad). The classified emotion is transmitted in real time to the chatbot response logic, which generates empathetic replies and personalized relaxation recommendations based on the detected mood. Primary data collection through questionnaires and interviews with 62 and 19 university students respectively confirmed the need for accessible digital mental health support. The results demonstrate that RoBERTa-based fine-tuning on conversational data provides a reliable foundation for real-time emotion-aware mental health chatbot systems.

The exponential growth of digital music catalogs on streaming platforms such as Spotify has made personalized recommendation systems crucial for enhancing user experience. This study develops a hybrid music recommendation system that addresses both warm-user and cold-user scenarios by combining Alternating Least Squares (ALS) collaborative filtering with content-based filtering (CBF) augmented by a popularity component. The dataset consists of 8,549,544 user-track interactions and a master file of 1,204,025 tracks with ten audio features. After preprocessing, users were segmented into 14,880 warm users and 723 cold users based on a five-interaction threshold. The ALS model was trained on the user-item implicit feedback matrix and tuned through grid search over factors, alpha, and regularization. CBF was implemented using cosine similarity on normalized audio features, while popularity scores were applied for new users with insufficient history. Evaluation used Precision@10, Recall@10, and NDCG@10. The final ALS configuration achieved NDCG@10 of 0.1116, representing a 30% improvement over baseline, while the hybrid CBF improved NDCG@10 for cold users from 0.0070 to 0.0201. Findings indicate that adaptive routing among ALS, CBF, and popularity reliably handles different user states, providing a practical foundation for production-grade music recommendation systems.

This study aims to analyze the management of Ikhwanul Ikhlas Wisata Travel in Medan in terms of pilgrim recruitment processes, manasik guidance patterns, assistance systems in the Holy Land, as well as indicators and evaluation of customer satisfaction. The background of this study is based on the increasing competition among Umrah travel agencies, which requires professional, transparent, and customer-oriented services to build trust and loyalty. In this context, Ikhwanul Ikhlas Wisata becomes an interesting case due to its consistency in guiding pilgrims from the initial stage to post-return.This research employs a qualitative approach with a descriptive method. Data were collected through in-depth interviews with three key informants representing management, the company director, and marketing personnel. Data analysis was conducted through data reduction, data display, and conclusion drawing to obtain a comprehensive understanding of Umrah travel management practices.The findings reveal that Ikhwanul Ikhlas Wisata implements a recruitment system that emphasizes transparency in package information, costs, facilities, and departure schedules. Manasik guidance is conducted through both theoretical and practical sessions on a regular basis and supported by competent tour leaders and mutawwif. Customer satisfaction is measured through indicators such as repeat participation, recommendations to family or relatives, and post-return testimonials. The evaluation of satisfaction is utilized as a foundation for continuous improvement in recruitment strategies, guidance patterns, and service quality.

This study aims to analyze the implementation of Good Governance principles—transparency, accountability, participation, effectiveness, efficiency, rule of law, and inclusivity—in public administration services at the Sungai Tabukan Sub-district Office, especially in the Service, Economy, and Social Welfare Section. The method used is a qualitative approach with a case study design through observation, in-depth interviews, and documentation of sub-district officials and service user communities. The data was analyzed through reduction, presentation, and conclusion drawn, and tested for validity by triangulation and member check techniques. The results of the study show that procedural transparency, compliance with SOPs, and administrative accountability mechanisms have been running relatively well, so that services such as SKKM, marriage recommendations, and population documents can be processed openly and can be traced. However, the limitations of human resources, facilities, and digital infrastructure cause the effectiveness and efficiency of services to still be conditional and depend on key actors. Community participation has been facilitated through forums and feedback channels, but it is still dominated by village intermediaries so that the direct involvement of residents is not optimal. In terms of the rule of law and inclusivity, services have been based on regulations and are non-discriminatory, although there are still inequality in access and speed of services between regions. The main supporting factors include leadership commitment, internal work culture, and the existence of SOPs, while inhibiting factors include limited human resources, facilities, and information systems that have not been integrated. It was concluded that the implementation of Good Governance in public administration services in Sungai Tabukan District has been running functionally, but has not been fully consolidated systemically. Therefore, it is necessary to strengthen policies through the digitization of services, increase the capacity of the apparatus, improve facilities, integrate data-based accountability and transparency systems, and expand citizen participation channels to realize more professional, fair, and sustainable public administration service.

This study aims to analyze innovative strategies that can be implemented by Micro, Small, and Medium Enterprises (MSMEs) in East Java to improve competitiveness through digital marketing and e-commerce. This study uses a descriptive qualitative approach with a library research method by reviewing various scientific literature, government reports, and previous studies related to MSME innovation and digital transformation. The results of the study indicate that digital marketing and e-commerce innovation can increase market reach, operational efficiency, product differentiation, and MSME sales. However, the implementation of innovation still faces several challenges such as low digital literacy, limited capital, limited technology, and lack of system integration. Therefore, innovative strategies are needed, including integrated digital marketing, marketplace optimization, social commerce, digital payment systems, logistics integration, digital branding strengthening, and digital literacy training. In addition, collaboration between MSMEs, government, universities, communities, and digital platforms is an important factor in accelerating MSME digital transformation. This study produces recommendations for an innovative strategy model based on digital marketing and e-commerce to improve the competitiveness and sustainability of MSMEs in East Java.

The architecture of consumer decision-making has completely changed due to the quick development of recommendation systems based on artificial intelligence (AI). The majority of earlier studies saw algorithms as instruments for forecasting and maximizing preexisting preferences. This study, however, makes a different claim: algorithmic curation actively shapes preferences rather than just reflecting them. This study creates and evaluates a structural model that examines the impact of algorithmic curation intensity on perceived search autonomy, identity resonance, affective evaluation, and the development of initial preferences. The model is based on identity-based consumption theory and the literature on human-AI interaction. The study's findings, which are based on survey data from Generation Z consumers and Structural Equation Modeling (SEM) analysis, demonstrate a contradictory dynamic: algorithmic curation improves identity resonance and directly influences initial preferences while simultaneously decreasing feelings of autonomy. The primary mediating mechanism that links algorithmic exposure to emotional assessment and preference creation is identified as identity resonance. In addition to introducing the concept of algorithmic consumer formation as a new conceptual framework for comprehending consumer behavior in the AI-based digital era, our findings expand the notion of bounded rationality toward algorithmically bounded agency.

This study analyzes the governance performance of information systems at the Career Center of Universitas Muhammadiyah Jambi using the COBIT 2019 framework. The primary objective is to evaluate the maturity level of IT governance and provide recommendations to enhance the efficiency and effectiveness of information systems in supporting the institution’s strategic objectives. Data were collected through interviews, observations, and questionnaires involving system users and decision-makers within the Career Center. The findings indicate that several areas require greater attention, particularly Managed IT Changes, Managed Risk, and Managed Operations. These domains are considered critical in improving the management and reliability of the existing information systems. The study also identifies several challenges affecting system performance, including limited system integration, insufficient human resources, and the use of outdated technology. Based on these findings, the research recommends strengthening the organizational structure, improving the competence of human resources, and optimizing IT processes in accordance with COBIT 2019 standards. Implementing these improvements is expected to increase IT governance maturity, enhance service quality for students and alumni, and better support the university’s strategic development goals.

Good governance has become a crucial framework for improving public sector effectiveness, accountability, and responsiveness to citizens’ needs. In Indonesia, decentralization policies since 1999 have devolved significant authority and resources to local governments, creating both opportunities and challenges in implementing good governance principles. This study examines administrative reform efforts in Indonesian local governments, focusing on progress, challenges, and key success factors. Using a multiple case study design, the research analyzed reform initiatives in six district/city governments with diverse contexts. Data were collected through document analysis, semi-structured interviews with government officials, civil society representatives, and citizens, as well as direct observation of administrative processes conducted between March and November 2024. The study assessed six core principles of good governance: participation, transparency, accountability, effectiveness and efficiency, equity and inclusiveness, and rule of law. The findings reveal variations in implementation across regions, with high-performing governments demonstrating strong leadership commitment, systematic planning, active citizen engagement, and effective monitoring mechanisms. However, challenges persist, including limited capacity, bureaucratic resistance, weak accountability enforcement, and low public participation. Key success factors include visionary leadership, capacity development, strategic partnerships, and institutional strengthening. Policy recommendations emphasize enhancing local capacity, accountability systems, citizen participation, and performance evaluation. Good governance has become a crucial framework for improving public sector effectiveness, accountability, and responsiveness to citizens’ needs. In Indonesia, decentralization policies since 1999 have devolved significant authority and resources to local governments, creating both opportunities and challenges in implementing good governance principles. This study examines administrative reform efforts in Indonesian local governments, focusing on progress, challenges, and key success factors. Using a multiple case study design, the research analyzed reform initiatives in six district/city governments with diverse contexts. Data were collected through document analysis, semi-structured interviews with government officials, civil society representatives, and citizens, as well as direct observation of administrative processes conducted between March and November 2024. The study assessed six core principles of good governance: participation, transparency, accountability, effectiveness and efficiency, equity and inclusiveness, and rule of law. The findings reveal variations in implementation across regions, with high-performing governments demonstrating strong leadership commitment, systematic planning, active citizen engagement, and effective monitoring mechanisms. However, challenges persist, including limited capacity, bureaucratic resistance, weak accountability enforcement, and low public participation. Key success factors include visionary leadership, capacity development, strategic partnerships, and institutional strengthening. Policy recommendations emphasize enhancing local capacity, accountability systems, citizen participation, and performance evaluation.

Bureaucracies worldwide face increasing pressure to innovate due to rising citizen expectations, technological disruption, and fiscal constraints. The digital era offers significant opportunities to transform public service delivery by overcoming traditional administrative barriers. This study employs a multiple case study design, analyzing 18 innovative public service initiatives in Indonesia recognized for service innovation. Data were collected through document analysis, semi-structured interviews, and direct observations. Using Innovation Diffusion Theory and Institutional Theory, the study examines innovation adoption, implementation, and sustainability. The findings show that successful bureaucratic innovations share six key characteristics: strong leadership, citizen-centric design, effective use of digital technologies, incremental implementation, institutionalization through regulations, and external partnerships. However, major barriers include rigid regulations, risk-averse organizational culture, fragmented authority, limited resources, inadequate digital infrastructure, and political influences. Digital technology plays a crucial enabling role, yet it must be supported by organizational change, capacity building, and cultural transformation. This study provides policy recommendations to support regulatory reform, strengthen innovation systems, and foster innovation-friendly public sector environments.

The effectiveness of public sector organizations in delivering quality services and achieving their mandates depends critically on how they manage their human resources. This study examines the relationship between strategic human resource management (SHRM) practices and organizational performance in Indonesian public sector organizations. Employing a mixed-methods research design, data were collected from 312 public sector managers and HR professionals across 45 government agencies through surveys and 32 in-depth interviews. The research investigates five key SHRM dimensions: strategic recruitment and selection, performance management systems, employee development and training, compensation and rewards, and employee engagement. Findings reveal significant positive relationships between SHRM practices and multiple performance indicators including service quality, operational efficiency, employee productivity, and organizational innovation. Regression analysis demonstrates that SHRM practices collectively explain 47.3% of variance in organizational performance scores. Qualitative data illuminate implementation challenges including limited HR professional capacity, rigid civil service regulations, political interference, and resistance to performance-based management. The study identifies critical success factors such as top management commitment, alignment between HR strategy and organizational strategy, investment in HR analytics capabilities, and cultural transformation toward merit-based practices. Results indicate that high-performing public organizations distinguish themselves through systematic talent management, data-driven HR decision-making, continuous learning cultures, and stronger linkages between individual performance and organizational outcomes. This research contributes empirical evidence on SHRM effectiveness in public sector contexts and provides actionable recommendations for HR practitioners and policymakers seeking to leverage human capital for improved public service delivery.

This study aims to analyze the implementation of Artificial Intelligence (AI)-based learning media and its implications for student learning motivation in Islamic Religious Education (PAI). This study uses a systematic literature review approach by examining various reputable scientific articles discussing the integration of AI in education and the dynamics of learning motivation in the context of PAI. The results of the study indicate that the use of AI through adaptive learning systems, educational chatbots, gamification, and learning analytics can increase the effectiveness, personalization, and interactivity of learning. This implementation has a positive impact on cognitive motivation through increased conceptual understanding, affective motivation through active participation and emotional engagement, and spiritual motivation through strengthening reflection and internalization of Islamic values. However, ethical challenges, the risk of depersonalization of the teacher's role, and inequality in digital access are crucial issues that require policy attention and human-centered pedagogical design. Theoretically, this study offers an integrative conceptual framework that combines technological innovation with Islamic educational epistemology. Practically, the results of this study provide recommendations for teachers, schools, and policymakers to develop AI-based PAI learning models that are adaptive, ethical, and oriented towards character building.