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This journal examines the Piriang Talam Bantiang dance attraction at Sanggar Talang Sarumpun as a form of performing art in the city of Payakumbuh. The method used is a descriptive-analytical qualitative research method, which involves presenting data obtained in the field and then analyzing it according to the research needs. This study employs the theory and opinions of Y. Sumadiyo Hadi regarding form to strengthen the writing. Additionally, it uses supporting theories from Dedi Supriadi on creativity. The results obtained from this research show that the Piriang Talam Bandantiang dance attraction is a form of performance that can attract the attention of the community to watch and enjoy, while simultaneously introducing Piriang Talam Bandantiang dance as a performing art in the region.

This research explores the potential of local bio-composites made from bamboo and coconut fiber as sustainable building materials in Indonesia. The construction sector in Indonesia faces significant environmental challenges, particularly the high carbon emissions associated with conventional materials like concrete and steel. The primary objective of this research is to evaluate the environmental and economic benefits of substituting these traditional materials with bio-composites, using Life Cycle Assessment (LCA) and energy optimization simulations. The LCA methodology evaluates the environmental impact of bio-composites across their entire life cycle, comparing them with conventional materials in terms of carbon emissions, energy consumption, and waste. Energy optimization simulations focus on assessing the thermal performance and overall building efficiency when using bio-composites in construction. The main findings suggest that bio-composites exhibit a significantly lower carbon footprint and better thermal insulation properties than concrete and steel, contributing to reduced energy consumption in buildings. Additionally, the use of locally sourced materials like bamboo and coconut fiber offers economic advantages, such as lower transportation costs and support for local economies. The research concludes that bio-composites can serve as viable alternatives to traditional materials, providing both environmental and economic benefits. For successful adoption, the research recommends policy support, technological advancements, and educational initiatives to promote the use of bio-composites in Indonesia’s construction industry.

This study explores the relationship between teachers' digital pedagogical competency and student learning outcomes in both rural and urban schools. A descriptive survey design, utilizing correlational and regression analyses, was employed to examine this relationship. Data were collected from teachers using a structured questionnaire assessing their digital competence, while student learning outcomes were measured through academic performance records. The results revealed significant differences between urban and rural schools in terms of teachers’ digital competence, with urban teachers demonstrating higher levels of digital skills. A positive correlation was found between teachers' digital competence and student learning outcomes, particularly in urban schools, where digital tools were more readily available. The regression analysis further confirmed that digital competence was a significant predictor of student achievement, with urban schools outperforming rural ones even after controlling for teacher experience. The study suggests that infrastructure availability, teacher training, and institutional support play crucial roles in enhancing digital competence, particularly in rural schools, where such resources are often limited. These findings underscore the need for policy reforms that ensure equitable access to digital tools and professional development opportunities for teachers across both rural and urban settings. Recommendations include targeted interventions for rural schools to bridge the digital divide and improve student learning outcomes through enhanced teacher digital competencies.

Measuring the company level of productivity performance is a very important thing to do to see and evaluate achievements and improvements to productivity levels that are not yet optimal. This case study was taken from the leather bag UKM which is currently experiencing a decline in productivity during the 2020 period. With the increase in working hours, the company must increase workers' overtime costs. In this research, the method used to measure the level of company productivity is the objective matrix or OMAX method and this research refers to the OMAX steps, namely determining productivity criteria on the production line, determining weights, determining levels on the objective matrix, calculating the productivity index, and productivity analysis with a traffic light system. The research results show that the average value of overall productivity in 2020 is 4,388 The highest productivity index was achieved in August amounting to 67,01%. From the traffic light system, it is known that the worst indicator of productivity is the defect factor, so improvements need to be made regarding this.

The rapid growth of cross-platform applications has significantly increased the volume and diversity of sensitive user data processed across heterogeneous and distributed environments. Personally identifiable information, device identifiers, behavioral data, and financial information are routinely collected to support personalization, analytics, and service optimization. While these practices enhance application functionality and user experience, they also introduce substantial privacy risks, including unauthorized data access, device fingerprint–based re-identification, cross-user data leakage, and large-scale data breaches. These risks are further amplified by distributed processing architectures and extensive third-party library integrations commonly used in modern cross-platform systems. This study aims to systematically analyze privacy issues in cross-platform applications by examining the types of sensitive data involved, identifying dominant privacy threats, and reviewing state-of-the-art privacy-preserving mitigation strategies. A systematic literature-based methodology was employed, focusing on recent Scopus-indexed journal articles, conference papers, and book chapters. The analysis synthesizes findings using thematic categorization and a conceptual research framework that maps sensitive data sources to privacy threats and corresponding mitigation mechanisms. The results indicate that privacy risks in cross-platform applications originate not only from external attacks but also from internal architectural weaknesses, such as flawed authorization logic and excessive data sharing across system components. Privacy-preserving techniques including differential privacy, federated learning, blockchain-based data governance, secure multi-party computation, and fine-grained access control mechanisms are shown to provide stronger privacy guarantees compared to conventional centralized approaches. However, these techniques also present trade-offs related to system complexity and performance. Overall, the study highlights the importance of adopting a multi-layered, privacy-by-design approach to ensure sustainable, trustworthy, and regulation-compliant cross-platform application development.

The increasing complexity and heterogeneity of data in Smart Information Systems pose significant challenges for effective decision-making. While data fusion techniques have been widely adopted to integrate multiple data sources, traditional fusion approaches often fail to consider contextual information, resulting in limited interpretability and reduced decision relevance. This study proposes a contextual data fusion approach that integrates heterogeneous data sources with contextual attributes, including temporal, spatial, and operational context, to enhance decision accuracy and robustness. The research employs a computational and experimental methodology involving data preprocessing, context encoding, multi-level data fusion, and performance evaluation. Experimental results demonstrate that the proposed approach outperforms single-source analysis and non-contextual data fusion in terms of accuracy, precision, recall, and F1-score, with only a marginal increase in computational cost. The findings confirm that incorporating context into the data fusion process significantly improves the quality and reliability of analytical outcomes. This study contributes to the development of intelligent and data-driven systems by highlighting the critical role of contextual awareness in supporting transparent and effective decision-making in Smart Information Systems.

The rapid growth of Internet of Things (IoT) and edge computing technologies has introduced new security challenges due to the distributed, heterogeneous, and dynamic nature of these environments. Conventional static security mechanisms, such as rulebased authentication and fixed trust models, are often inadequate for addressing evolving threats and abnormal behaviors in largescale IoT systems. To overcome these limitations, this study proposes a machine learningbased trust evaluation framework for enhancing security in distributed IoT environments. The proposed approach dynamically assesses the trustworthiness of IoT nodes by analyzing behavioral and interactionbased features collected at the edge layer. Machine learning models are trained to classify nodes into trusted and malicious categories and continuously update trust values in response to changing network conditions. Based on the predicted trust levels, adaptive security decisions are enforced to allow or restrict node participation in data sharing and computation processes. A quantitative experimental evaluation is conducted using simulated distributed IoT scenarios that include both normal and malicious behaviors. The performance of the proposed framework is evaluated using standard metrics such as accuracy, precision, recall, F1score, and detection effectiveness, and is compared against conventional static trust and rulebased security mechanisms. The results demonstrate that the proposed machine learningbased trust evaluation approach achieves significantly higher detection accuracy and robustness while maintaining low computational overhead. Overall, the findings confirm that integrating machine learning into trust management provides an effective and scalable solution for securing distributed IoT systems under dynamic and adversarial conditions.

Artificial Intelligence (AI)-based Decision Support Systems (DSS) have become a central component of digital transformation initiatives across various industries. While prior studies have primarily emphasized technical aspects such as accuracy, performance, and computational efficiency, less attention has been given to the integration of human-centered principles and scalable architectural design. This study aims to examine how AI-based DSS can be enhanced through the combined application of Human-Centered Artificial Intelligence (HCAI) principles and scalable AI architecture. Using a qualitative, literature-based research methodology, this study systematically analyzes peer-reviewed publications indexed in Scopus to identify key dimensions influencing the effectiveness and sustainability of AI-driven DSS. The findings indicate that technical capabilities alone are insufficient to ensure successful adoption and long term impact. Instead, transparency, explainability, ethical governance, and user empowerment core elements of HCAI are critical for fostering trust and user acceptance. Furthermore, scalable architectural principles, including modularity, interoperability, and adaptability, are essential for enabling AI-based DSS to operate reliably in large-scale and dynamic environments. This study contributes a unified conceptual framework that bridges technical scalability and human-centered design, offering theoretical insights and practical guidance for developing trustworthy, scalable, and sustainable AI-based Decision Support Systems in digital transformation contexts.

The study conducted at the National Potential Young Athletes Training Center (SLOMPN) of Unesa provides a crucial perspective on the use of an Android-based match statistics application. The research aims to optimize athletes' potential through the Long Term Athlete Development (LTAD) approach, integrating knowledge of athlete development with the application of technology in training. The survey results from 5 coaches indicate that the application aids in planning training, understanding application features, and assessing athlete development with positively skewed average scores. However, there is room for improvement, especially in terms of comfort during matches and communication with athletes. Meanwhile, 18 athletes showed positive acceptance of the application by rating its ease of use and impact on performance enhancement highly. Nevertheless, there is a need for improvement in injury recovery features and data security. This study underscores the importance of continuous collaboration between application developers and users to enhance the effectiveness of technology in sports training.

This research aims to explore public responses regarding the existence of mental health applications. This research was conducted using descriptive qualitative phenomenological methods. This research uses a phenomenological approach with data collection techniques using focus group discussions and interviews. The object of this research was students aged 16-22 years and who had experience with mental health. The data obtained came from 8 people in FGDs and 16 people in interviews with a trial period of 3-4 weeks. The results of the research show that the user interface has an effect on the user's perspective, application performance has an effect on the intention to use it continuously, emotional release has an effect on changes in individual behavior.

The canned food industry is experiencing growth in this modern era. Canned food has become a popular choice due to its convenience in storage and preparation. Canned food manufacturers continue to develop new products and improve the quality of existing products to meet the increasingly diverse consumer demand. Challenges in improving company performance require companies in the canned food industry to constantly enhance the performance of their supply chains to remain competitive in the global market. This research aims to measure the performance of the canned food industry supply chain by implementing SCOR and integrating it with AHP. Based on the performance measurement results, PT XZY, a canned food company, has a SCOR score of 76.58, indicating that the company's performance is considered good. The lowest KPIs are Delivery performance and Return performance.

This study investigates the performance and sustainability of a hybrid solar-biomass drying system for agricultural products, focusing on its efficiency, environmental impact, and economic feasibility. The hybrid system combines solar energy and biomass combustion to create a continuous and reliable drying process. The key findings reveal that the hybrid system achieves over a 20% improvement in drying efficiency compared to solar-only and biomass-only dryers. This efficiency gain is attributed to the synergistic use of solar energy during the day and biomass energy during periods of low sunlight or at night, ensuring consistent drying conditions and reduced drying time. Additionally, the hybrid system significantly reduces CO₂ emissions, contributing to a more sustainable approach to agricultural processing. The environmental benefits of using renewable energy sources, as opposed to fossil fuels, align with the growing need for energy-efficient and eco-friendly agricultural technologies. Economic analysis suggests that the hybrid system is a cost-effective solution for small- to medium-scale farmers, particularly in rural areas where access to grid electricity is limited. The use of locally available biomass fuels further enhances the system’s sustainability and affordability. This study also discusses the practicality of implementing hybrid dryers in rural farming communities, emphasizing their potential to improve drying efficiency, reduce environmental impacts, and boost economic opportunities for farmers. Future research should focus on optimizing system integration, expanding biomass fuel options, and exploring automation to enhance the performance and scalability of hybrid drying systems.

This study investigates the contribution of Islamic banks in supporting green economy initiatives and promoting sustainable financial growth. Employing a quantitative research design, the study utilizes secondary data collected from annual reports, sustainability disclosures, and carbon emission reports of Islamic banks for the period 2018–2024. The research aims to examine the relationship between green financing portfolios and key financial performance indicators Return on Assets (ROA), Return on Equity (ROE), and Capital Adequacy Ratio (CAR) while evaluating the environmental impact through carbon emission reduction. Descriptive statistics provide an overview of green financing activities and financial ratios, while multiple regression analysis assesses the effect of green financing on sustainable financial performance, controlling for bank size, Gross Domestic Product (GDP) growth, and inflation. An independent sample t-test compares Islamic and conventional banks in terms of ethical compliance, environmental contribution, and profitability. The findings reveal that Islamic banks allocate a higher proportion of financing to green projects, achieving significant carbon emission reductions without compromising financial performance. The green financing portfolio exhibits a positive and significant effect on sustainable financial growth, and larger banks demonstrate a greater capacity to implement sustainability initiatives. The comparative analysis confirms that Islamic banks outperform conventional counterparts in environmental and ethical dimensions while maintaining comparable profitability. These results underscore the potential of Sharia-compliant banking to integrate ethical, environmental, and economic objectives, positioning Islamic financial institutions as key actors in advancing a sustainable, low-carbon financial system.

This study investigates sustainable Islamic business models through a qualitative case study of green-tech startups in Central Java, Indonesia. Using semi-structured interviews with founders, managers, and employees, complemented by secondary data from business reports and sustainability disclosures, the research examines how Islamic ethical principles, including stewardship (khalifah), social welfare (maslahah), and justice (adl), are integrated into operational practices and sustainability strategies. The purposive selection of 3–5 startups enables an in-depth exploration of organizational decision-making, innovation adoption, and environmental and social performance. Thematic analysis identifies recurring patterns in ethical integration, technological innovation, and sustainability outcomes. Findings reveal that Islamic startups effectively embed ethical values into operations, fostering environmental accountability through renewable energy initiatives, waste reduction, and resource optimization, while enhancing community engagement and equitable service delivery. Technological innovations such as IoT, AI, and blockchain further support sustainability performance, enabling startups to monitor and optimize environmental outcomes without compromising financial viability. Comparative analysis demonstrates that Islamic startups outperform non-Islamic counterparts in key sustainability metrics, including carbon reduction and social impact, highlighting the competitive advantage of ethics-driven entrepreneurship. Overall, the study confirms that Islamic ethical frameworks foster both environmental accountability and technological innovation, providing a practical model for sustainable development in emerging economies. These findings offer valuable insights for policymakers, investors, and entrepreneurs seeking to align ethical, social, and environmental objectives with business strategy.

This study examines the application of sharia economic principles in the photocopying and office stationery (ATK) business in the pesantren environment, focusing on business performance that is not only financially profitable but also has a positive impact on society and the environment. Using a qualitative approach, this study analyzes current business practices as well as strategies that can be applied to integrate sharia values, such as the prohibition of riba, gharar, and maysir. The findings of the study show that the application of sharia economics can improve business performance through capacity building, cooperation with Islamic financial institutions, and technology adoption.

An internal combustion engine is a device that functions to convert thermal energy from burning fuel into mechanical energy. The Cdi ignition system is an electronic ignition system that works by utilizing a capacitor charge and discharge. CDI variations have an influence on engine torque on motorcycle engines. At 5700 rpm the motor uses a standard CDI the resulting torque is 7.11 Nm, and on a racing CDI the torque generated is 7.45 Nm at 5900 rpm. The standard CDI generated power is 6.64 hp at 7500 RPM, pan at the resulting CDI racing power is 6.79 at 7300 RPM. From the results above the standard and racing power has a difference of (2.25%) and the standard and racing torque has a difference of (4.78%). Overall using this CDI is designed to be more aggressive than standard CDI. of the two CDIs that have been tested, the racing cdi has a performance value on a 100cc Honda Supra motorcycle engine.

Environmental degradation and poverty remain pressing challenges in Indonesia, exacerbated by rapid economic growth and resource exploitation. The increasing demand for sustainable development has highlighted the need for alternative financial models that integrate both economic growth and environmental protection. Sharia-based green investments have emerged as a promising solution, offering a framework that aligns ethical considerations with sustainability goals. This study examines the impact of Sharia-based green investments on social welfare and environmental sustainability in Indonesia, with a focus on reducing income inequality and fostering community development. Using a mixed-method approach, including quantitative analysis of secondary data on green investment performance and qualitative interviews with key stakeholders, the research evaluates how these investments contribute to enhancing income equality, providing access to renewable energy, and promoting sustainable economic activities. Findings show that Sharia-based green investments not only improve income distribution, especially in rural areas and small businesses, but also contribute to environmental sustainability through renewable energy projects and eco-friendly infrastructure. The study also compares the environmental benefits of Sharia-based investments with conventional models, emphasizing their superior alignment with long-term sustainability goals. The research underscores the potential of Sharia-based green investments as a model for inclusive economic growth and environmental protection, supporting Indonesia’s progress toward achieving the Sustainable Development Goals (SDGs).

The development of modern companies often leads to overlapping functions between departments, such as the dualism of functions between Human Resources (HR) and financial accounting. This creates serious challenges in resource management and accounting that can impact the overall performance of the organization. Issues faced include overly simplistic financial recording due to HR's lack of expertise in accounting, as well as the risk of errors and data inaccuracies. This research aims to provide in-depth insights into the impact of HR and financial accounting dualism at PT. Segi Muda Bertiga and identify solutions to enhance the efficiency and accuracy of resource and financial management. The research method employs a qualitative approach, analyzing five main theoretical studies, including cash sales accounting systems, payroll and wage analysis, cash receipts, inventory, and purchases. Data is gathered through interviews, literature reviews, and document analysis.    

This article explores the influence of parental involvement on students' academic achievement across various cultural contexts. By comparing involvement strategies in different countries, the study examines how cultural factors impact parental roles in children's education. Findings indicate that parental engagement significantly boosts academic performance, although the effectiveness of different engagement strategies varies based on cultural norms, socioeconomic status, and parental education levels.

The Tridharma of Higher Education contains three important points, namely education, research and community service. Community service on this occasion was carried out with partners from Ar Rahman Junior School. Current technological developments, especially computer technology, are very advanced. In Indonesia, many computer products are marketed with various types, prices and specifications. The computer hardware component manufacturing industry competes with each other to satisfy consumers and customers. Computer assembly and installation are important processes in the development and maintenance of efficient and reliable computer systems. In-depth knowledge of assembly and installation procedures is key to ensuring optimal performance as well as system safety. For this reason, there is a need for computer assembly and installation training for students at Ar Rahman junior School who have the knowledge and skills in assembling and installing their own computers properly and are able to implement it at school.