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The Indonesia Smart Program (Program Indonesia Pintar/PIP) is a government initiative aimed at ensuring equal access to education for students from underprivileged families, including those at the junior high school (SMP) level. However, at the school level, the management of PIP recipient data still faces several challenges, particularly in data searching and utilization, due to the increasing volume of data and the use of simple or manual search methods. These conditions can lead to delays in obtaining information and reduce the accuracy of decision-making. Therefore, an effective information retrieval system is needed to manage and search PIP recipient data efficiently. This study aims to design and develop an Information Retrieval System for PIP recipient data at the junior high school level using the Term Frequency–Inverse Document Frequency (TF-IDF) method. The TF-IDF method is applied to assign weights to terms in each document, enabling the system to identify and rank documents based on their relevance to user queries. The test results show that the system is able to measure document relevance accurately, where documents D3 and D4 obtain the highest similarity value of 0.099586089 and are classified as highly relevant, while other documents show lower similarity values down to zero. These results are also supported by graphical visualization, which helps users compare relevance levels more clearly. Thus, the implementation of the TF-IDF method has proven to be effective in supporting accurate, efficient, and systematic searching and management of PIP recipient data at the junior high school level.

Micro-entrepreneurs, particularly small grocery shop owners, commonly encounter challenges in managing business finances and implementing effective marketing strategies. Limited skills in financial recordkeeping often make it difficult for business owners to accurately monitor cash flow and assess their financial condition, which may lead to suboptimal business decisions. In addition, the utilization of digital technology as a marketing tool remains limited, thereby restricting opportunities for market expansion. This community service program aims to strengthen the capacity of micro-enterprises in applying practical basic financial management and optimizing digital platforms for product promotion. The program also seeks to increase awareness of the importance of structured financial management as a foundation for sustainable business development. The activities were conducted through several stages, including the delivery of material on the significance of financial recording, hands-on training sessions, mentoring in preparing simple financial records, and digital marketing simulations using WhatsApp Business and various social media platforms. The results indicate an improvement in participants’ understanding and skills in recording income and expenses, managing business capital more systematically, and utilizing digital features to support promotional activities. Furthermore, participants demonstrated a more positive attitude toward the adoption of technology in their daily business operations. Overall, this program is expected to enhance financial independence, support sustainable business growth, and expand the marketing reach of micro-enterprises

Model driven Development (MDD) has emerged as an efficient software engineering methodology that focuses on using high-level models as primary artifacts throughout the software development process. The methodology involves transforming abstract models into detailed designs, and eventually into executable code, with the assistance of automated tools. This study evaluates the impact of MDD on the Verification and Validation (V&V) processes within secure enterprise software systems. By comparing MDD-based projects with traditional code-centric development approaches, the study highlights the advantages of MDD in reducing verification time, minimizing defect leakage, and improving the traceability of security requirements. MDD significantly enhances V&V efficiency by automating key processes, which allows for earlier error detection and better resource utilization. Additionally, MDD strengthens security compliance by integrating security requirements early in the development lifecycle, ensuring better alignment between system requirements and their implementation. Despite the clear benefits, challenges such as the lack of standardized tools and the need for specialized expertise in model development were also encountered during the study. The findings of this research offer important insights for enterprise software development teams looking to adopt MDD for more efficient and secure V&V processes. Future research should focus on the long-term impact of MDD on security compliance, as well as its adoption across different industries, to fully understand the practical benefits and challenges of implementing MDD in diverse real-world environments.

The increasing demand for real time parallel processing in cloud computing environments necessitates the development of more efficient and fault-tolerant scheduling algorithms. Traditional scheduling methods, such as static algorithms, often fall short when handling dynamic workloads and system failures, leading to increased task latency and reduced system performance. In contrast, adaptive scheduling algorithms dynamically adjust to changes in system conditions and workloads, ensuring timely task completion and optimized resource utilization. This study evaluates the performance of adaptive scheduling algorithms in real time cloud environments, focusing on key factors such as task latency, system resilience, and fault tolerance. Simulation experiments were conducted using cloud computing models that incorporate fault injection scenarios, including network failures and virtual machine crashes. The results show that adaptive algorithms significantly outperform traditional static schedulers in terms of task latency reduction and improved system resilience. These algorithms demonstrated better fault recovery times and ensured consistent real time performance, even under failure conditions. The findings highlight the advantages of adaptive scheduling in cloud environments, particularly for applications requiring rapid data processing and high system reliability. Despite the promising results, challenges remain regarding the scalability and complexity of these algorithms in large-scale cloud systems. Further research is needed to optimize adaptive scheduling algorithms for efficiency, scalability, and comprehensive performance evaluation, taking into account factors such as energy consumption, cost, and reliability. This research contributes to advancing cloud computing infrastructures that can dynamically handle real time tasks and maintain high performance under varying workloads and failures.

The utilization of digital technology in the Industry 4.0 era has become crucial for vocational high school (SMK) students to build economic independence. However, partners at SMKN 1 Selo still face obstacles in optimizing social media and digital platforms as effective promotional tools for student work and self-development. This community service activity aims to enhance students' understanding and skills in using social media (Instagram, TikTok) and other digital platforms as creative marketing instruments. The method employed is a descriptive qualitative approach through participatory training, which includes material presentation on digital branding strategies, visual content creation practices, and copywriting techniques. The results of the activity indicate a significant improvement in students' technical abilities, where they demonstrated the capacity to produce engaging promotional content and understand social media algorithms to reach a wider audience. This study aims to describe the process and impact of utilizing social media and digital platforms as promotional tools for SMKN 1 Selo students. The primary focus of this activity is to provide a deep understanding of personal branding strategies and creative product marketing in the digital age. Through this program, it is expected that SMKN 1 Selo students will possess higher digital competitiveness and the ability to leverage the digital ecosystem to support the promotion of vocational products and their professional profiles in the future.

The development of information technology encourages organizations to adopt a more efficient, flexible, and secure data management system, especially in the field of financial management that requires high accuracy and reliability. One of the technologies that is widely used is cloud computing, which offers easy access to data and an integrated security system. This article aims to analyze the utilization of cloud technology in improving the security and accessibility of financial management data. The method used in this study is a literature study by examining various scientific sources, books, and online news relevant to the topic of cloud computing and financial data management. The results of the study show that cloud technology is able to improve data security through the implementation of encryption, multi-layered access control, user authentication, and a reliable data backup system. In addition, cloud technology also improves the accessibility of financial data because it allows users to access information in real-time, flexibly, and without location or device restrictions. Thus, the application of cloud technology can be a strategic solution for organizations in improving operational efficiency, data security, and the quality of decision-making in financial management.

The increasing demand for low latency and high-throughput multimedia applications has spurred significant advancements in hardware software co design. This study explores the integration of custom digital signal processing (DSP) hardware accelerators with optimized software frameworks to enhance deep learning accelerated DSP tasks. The proposed co design approach significantly reduces latency and improves throughput compared to traditional software-only DSP implementations. Through the development of custom hardware accelerators built with FPGA technology, the system achieves up to a 1.85x reduction in latency and a 1.5x improvement in throughput for real-time multimedia tasks such as image recognition, video decoding, and audio processing. The combination of hardware and software optimizations allows for better resource utilization, enabling the parallel processing of computationally intensive tasks while the software framework handles less demanding operations. Additionally, the co design system demonstrated improved energy efficiency, making it highly suitable for embedded systems. The results show that the hardware software co design approach offers substantial advantages in performance, latency reduction, and energy efficiency, positioning it as a viable solution for real-time multimedia applications. The findings have important implications for applications requiring fast data processing, such as autonomous driving, healthcare, and disaster management. Future research could explore alternative hardware accelerators, advanced software optimizations, and AI-based resource management to further improve the system’s efficiency and scalability for more complex multimedia tasks.

Technology-based learning media have now become a primary choice in supporting the learning process in elementary schools, in line with the development of the digital era and the growing demand for more innovative learning approaches. The utilization of technology in education is expected to enhance the quality of teaching and learning processes and encourage active student engagement. One technology-based learning medium considered effective and engaging is BrainPOP, a digital learning platform that presents educational content through interactive animated videos, quizzes, simulations, and various supporting activities designed to suit the characteristics of elementary school students. The selection of BrainPOP is based on its advantages in increasing students’ learning interest, facilitating the understanding of abstract concepts by making them more concrete, and enhancing students’ motivation and retention of learning materials. The visual, communicative, and interactive presentation of content enables students to learn in a more enjoyable and less monotonous manner. This medium is capable of creating an engaging, effective, and student-centered learning atmosphere, thereby fostering an active, creative, and enjoyable learning environment. Therefore, the use of BrainPOP in the learning process is expected not only to improve students’ learning outcomes but also to optimally and sustainably develop their interest, motivation, and engagement in learning.

This community service activity aims to enhance students’ literacy through the application of ecoprint as an environmentally based creative learning medium at MAT Daarut Tahfidz Al-Ikhlas Banda Aceh. This program was motivated by the limited utilization of practice-based art activities as a means of strengthening students’ literacy. The implementation method employed a participatory-educative approach consisting of material socialization, ecoprint technique demonstrations, group-based hands-on practice, reflective discussions, and activity evaluation. The results indicate that students were able to understand the concepts and stages of ecoprint, produce works with various natural motifs, and demonstrate improvements in visual literacy and creativity. In addition, the activity increased students’ awareness of the use of natural materials and the importance of environmental friendly practices. Group-based activities also encouraged the development of social literacy through collaboration and communication among participants. Therefore, ecoprint can be considered an effective and contextual alternative learning medium to support the enhancement of students’ literacy in the school environment and has the potential to be sustainably developed.

The integration of Customer Relationship Management (CRM) and Enterprise Resource Planning (ERP) systems has emerged as a critical strategy for modern digital enterprises aiming to enhance customer experience and operational efficiency. This study examines the impact of CRM-ERP integration on customer satisfaction, personalized service, and organizational responsiveness. By adopting a mixed-methods approach, this research combines quantitative customer data analysis and qualitative managerial interviews to assess the benefits and challenges of CRM-ERP integration. Key findings highlight significant improvements in customer experience, with increased satisfaction and personalized interactions facilitated by a unified view of customer data. Operational efficiencies were also realized through streamlined processes, better alignment of departments, and enhanced decision-making based on real-time, data-driven insights. Despite these positive outcomes, challenges such as system integration complexities, data fragmentation, and resistance to change were identified, which hindered the speed of integration and full utilization of the systems. This study demonstrates that CRM-ERP integration provides a competitive advantage by improving both customer service and business agility, particularly in industries undergoing digital transformation. For digital enterprises, integrating these systems is crucial for maintaining a seamless customer experience across various touchpoints and achieving greater operational effectiveness. The paper concludes by suggesting future research on the long-term impact of CRM-ERP integration on customer loyalty, business growth, and the potential role of emerging technologies like AI and blockchain in further enhancing these systems.

Production planning and inventory control are critical aspects of operations management, as they directly influence cost efficiency, resource utilization, and the continuity of the production process. Ineffective planning and inventory decisions may lead to excessive costs, production delays, or imbalances between supply and demand. The complexity of these problems, which often involve multi-period horizons and multi-stage decision-making processes, has encouraged the application of quantitative optimization methods, one of which is dynamic programming. This study aims to analyze and synthesize the application of dynamic programming in production planning and inventory control through a Systematic Literature Review (SLR) approach. The SLR process was conducted by systematically identifying, selecting, and analyzing 15 relevant national journal articles published between 2015 and 2024 and obtained from various recognized scientific databases. The reviewed literature indicates that dynamic programming is effective in supporting optimal decision-making by determining appropriate production quantities and inventory levels, minimizing total production and holding costs, and managing fluctuating demand conditions. In addition, this method helps reduce the risks associated with overstock and stockouts by considering sequential decision structures. However, the findings also reveal several limitations of dynamic programming, including high computational complexity, strong dependence on deterministic data assumptions, and limited flexibility in handling high levels of uncertainty. These constraints suggest the need for further methodological development or integration with other approaches to enhance practical applicability.

This research focuses on the design and evaluation of a novel parallel graph optimization algorithm incorporating dynamic load balancing (DLB) to address inefficiencies in heterogeneous computing environments. Large-scale graph optimization problems, such as those in social networks, bioinformatics, and transportation systems, often suffer from computational imbalances when using traditional static load balancing approaches, leading to underutilized resources and prolonged execution times. The primary objective of this research is to develop an algorithm that can dynamically adjust workload distribution across processors, enhancing computational efficiency and scalability. The proposed method combines heuristic techniques, including region expansion and multilevel partitioning, with diffusive load balancing strategies to minimize inter-processor communication overhead. Experimental results demonstrate that the proposed algorithm reduces execution time by up to 40% compared to static methods, with optimized resource utilization and more balanced workload distribution. The scalability of the algorithm is also evident, as it adapts effectively to increasing problem sizes and processor counts. These findings suggest that dynamic load balancing is crucial for improving parallel graph optimization in real-world applications. Future work will focus on further enhancing the algorithm’s responsiveness to rapidly changing workloads and expanding its applicability to additional domains.

This study investigates the determinants of capital structure within the healthcare industry, focusing on the influence of asset structure, profitability, and company size. Given the capital-intensive nature of healthcare—characterized by significant investments in medical technology and infrastructure—understanding how these firms balance debt and equity is critical for financial sustainability and operational growth. Using a quantitative approach, this research analyzes a panel dataset of healthcare companies listed on the Indonesian Capital Market from 2018 to 2023. Furthermore, the capital structure is quantified by the debt-to-equity ratio. Meanwhile, asset structure, profitability, and company size are measured by the ratio of fixed assets to total assets, return on assets, and the natural logarithm of total assets, respectively. Moreover, the data are analyzed using multiple linear regression, supported by the classical assumption testing. As a result, asset structure has a significant positive impact on capital structure, aligning with the static trade-off theory. Conversely, profitability demonstrates a significant negative relationship with capital structure, supporting the pecking order theory. Finally, company size positively affects capital structure, indicating that larger firms have greater access to debt financing. These findings suggest that healthcare managers should optimize their asset utilization and internal reserves to maintain an efficient capital structure that supports long-term healthcare delivery and investor confidence.

Plastic waste is a form of solid waste originating from synthetic polymer materials that are difficult to decompose naturally and pose serious threats to environmental sustainability. Its accumulation continues to increase, causing pollution of soil, water, and ecosystems. In general, public attention is often limited to waste disposal and management activities without addressing preventive measures or innovative solutions at the source of the problem. This study aims to increase public awareness of plastic waste processing as an alternative approach to reducing the growing volume of plastic waste generated daily. One promising method explored in this research is the utilization of plastic waste as a raw material for producing environmentally friendly construction bricks. The study applied a simple descriptive experimental approach through direct practical activities, including the collection of plastic waste, processing and melting procedures, molding processes, and drying stages. The results demonstrate that plastic waste can be transformed into bricks with adequate physical strength and mechanical properties that comply with basic building standards. Therefore, this method has the potential to support sustainable waste management while providing alternative construction materials.

The increasing incidence of violence against women and children requires an active and effective role of public organizations in providing sustainable protection. This study aims to analyze the role of the Population Control, Women’s Empowerment, and Child Protection Office (DP5A) of West Sumba Regency in handling cases of violence against women and children. The research employs a descriptive qualitative approach. Data were collected through interviews, observations, and document analysis from purposively selected informants and analyzed using data reduction, data presentation, and conclusion drawing, supported by source and technique triangulation. The findings indicate that DP5A has performed its facilitative, educational, representative, and technical roles; however, their implementation has not been optimal. Major obstacles include limited facilities such as the absence of a permanent safe house, inadequate operational infrastructure, limited human resource capacity, underutilization of information technology and digital media, as well as cultural and administrative constraints. This study concludes that institutional strengthening, capacity building of personnel, optimization of technology utilization, and enhanced cross-sector collaboration are essential to improve the effectiveness of protection for women and children at the local level.

The management of material and labor costs at Gregors Barbershop is still manual and not formally structured, resulting in wastage of consumable materials, suboptimal labor utilization, and difficulties in determining service prices that align with the expected profit margins. Material costs, such as hair gel, tissues, disposable razors, and alcohol/disinfectants, are not recorded systematically, leading to frequent mismatches between stock and actual needs, while labor costs are calculated improvisationally without considering productivity and service targets. This activity aims to improve the ability of owners and employees to plan, control, and evaluate operational costs systematically, ensuring efficiency, resource optimization, and business profitability. The method uses an applied, hands-on approach, including the identification of partner needs, preparation of relevant training modules, direct operational mentoring, and evaluation with follow-up. The object of the activity is Gregors Barbershop in Batu Aji District, Batam City, which offers services such as modern men’s haircuts, classic shaves, shaving, hair treatments, and the sale of grooming products like pomade and hair oil. The results show increased efficiency in the use of consumable materials, more productive labor management, more systematic cost planning, and the ability to set service prices in line with costs and profit margins. It is recommended to implement a digital recording system and productivity-based incentives to ensure more accurate cost control, more efficient operations, and sustainable business profitability.

This community service program aims to analyze the effectiveness of utilizing TikTok Shop as a digital marketing platform for UMKM Izzata Hijab located in Paciran District, Lamongan Regency. The main problem faced by the partner is the suboptimal management of digital marketing, particularly in content strategy planning, posting consistency, and the utilization of TikTok Shop features, resulting in marketing activities that have not yet provided maximum impact on improving marketing performance. The implementation method of this community service employed a mentoring and training model, which included stages of interviews, observation, and documentation throughout the mentoring process. The results indicate that the planned and sustainable implementation of digital marketing strategies through TikTok Shop is able to increase brand awareness, expand promotional reach, enhance customer interaction, and positively impact product sales. The effectiveness of the community service program is influenced by posting consistency, visual content quality, digital communication understanding, and the partner’s responsiveness to customers. This community service confirms that TikTok Shop digital marketing assistance is an effective strategy in supporting the improvement of marketing performance of UMKM Izzata Hijab in the digital era.

This study aims to examine the effect of Corporate Social Responsibility (CSR) costs and financial characteristics on tax avoidance practices among publicly listed companies with the largest market capitalization in Indonesia. The study is motivated by Indonesia’s relatively low tax ratio compared to other emerging economies in the ASEAN region, which suggests the persistence of tax avoidance practices, particularly among large corporations. Grounded in legitimacy theory and agency theory, this research empirically investigates the influence of CSR costs, profitability, leverage, liquidity, activity ratio, growth ratio, and operating cash flow on tax avoidance. The research sample consists of 50 companies with the largest market capitalization listed on the Indonesia Stock Exchange over the 2020–2024 period, employing a census sampling method and unbalanced panel data. Secondary data were obtained from annual financial reports and analyzed using panel data regression techniques. Tax avoidance is measured using the Book-Tax Differences (BTD) approach, while model selection is determined through the Chow test, Hausman test, and Lagrange Multiplier test. The results indicate that, simultaneously, all independent variables have a significant effect on tax avoidance. Partially, the activity ratio has a negative effect on tax avoidance, whereas the growth ratio and operating cash flow have a positive effect on tax avoidance. Meanwhile, CSR costs, profitability, leverage, and liquidity do not show a significant effect. These findings suggest that asset utilization efficiency tends to restrain tax avoidance behavior, while corporate growth dynamics and strong operating cash flows encourage more aggressive tax management strategies. This study provides empirical evidence from an emerging market context and offers insights for tax authorities and regulators in designing more effective, risk-based tax supervision policies.

Listening skills are fundamental in English language learning because they are the main gateway to language proficiency. However, students often face obstacles such as differences in accents, the speed of native speakers, and limited vocabulary. This study aims to describe the use of the Spotify application as a learning medium to improve students' listening skills. This study uses a descriptive qualitative approach. The research subjects were third-semester students of the English Education Study Program at UIN Sumatera Utara (UINSU) in class TBI 2. Data were collected through questionnaires covering content usage patterns, duration, and application feature utilization. The results showed that: Students actively use Spotify (music and podcasts) as a source of authentic language input independently. Using Spotify has a positive impact on vocabulary comprehension, pronunciation, intonation, and conversation comprehension skills. The playback speed feature helps students control the audio speed according to their ability level, making the learning process more flexible and personalized. Consistent listening duration (15–30 minutes) is effective in supporting the development of listening skills without causing cognitive fatigue.

This study aims to analyze the influence of auditor competence, independence, and the use of audit technology on the quality of internal audits of Regional Inspectorates and their impact on the accountability of regional financial governance. Using a quantitative approach, this study involved 154 internal auditors from three regions who were analyzed using an explanatory survey method. The data analysis method used was multiple and simple linear regression to test the relationship between variables. The results showed that auditor competence had a positive and dominant influence on internal audit quality (β = 0.402, p = 0.000), independence also had a positive influence (β = 0.298, p = 0.000), while the use of audit technology had a limited positive influence (β = 0.187, p = 0.011). Furthermore, audit quality was proven to have a significant influence on the accountability of regional financial governance with a value of β = 0.588 and R² = 0.531. These findings confirm that better internal audit quality, influenced by higher auditor competence, strong independence, and more optimal utilization of audit technology, is a key prerequisite for achieving accountability in regional financial governance.