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Human–Robot Interaction (HRI) systems increasingly rely on data-driven approaches to interpret multimodal sensory inputs and support natural interaction. However, purely neural-based HRI models often suffer from limited interpretability and insufficient context-aware decision-making, which can reduce user trust and adaptability in dynamic interaction scenarios. To address these limitations, this study proposes a hybrid neural–symbolic HRI framework that integrates multimodal neural perception with explicit symbolic reasoning for adaptive and interpretable robot behavior. The proposed system combines deep neural networks for processing visual, speech, and gesture inputs with a rule-based symbolic reasoning layer that models interaction context, user states, and behavioral constraints. A loosely coupled integration strategy enables neural outputs to be transformed into symbolic representations, allowing logical inference to guide action selection while preserving perceptual accuracy. The framework was evaluated through controlled HRI experiments comparing a neural-only baseline with the proposed hybrid configuration across multiple interaction scenarios. Experimental results demonstrate that the hybrid neural–symbolic system significantly improves interaction accuracy, contextual responsiveness, and user satisfaction, while achieving substantial gains in interpretability. These findings indicate that symbolic reasoning effectively complements neural perception by enhancing transparency and context-aware adaptation without compromising performance. The study concludes that hybrid neural–symbolic architectures provide a promising foundation for developing trustworthy, adaptive, and human-centered HRI systems.

Recent advancements in environmental monitoring and robotic control demand systems that are capable of real-time responsiveness, energy efficiency, and reliable operation in dynamic and resource-constrained environments. Conventional cloud-centric cyber-physical system (CPS) architectures often suffer from high latency, continuous connectivity dependency, and increased energy consumption, limiting their suitability for time-critical monitoring and adaptive control applications. To address these challenges, this study proposes an intelligent embedded cyber-physical system integrating Edge AI, low-power sensor networks, and adaptive robotic control for environmental monitoring. The proposed architecture relocates data processing and decision-making closer to the data source, enabling real-time inference, reduced communication overhead, and enhanced system autonomy. The research adopts a design-oriented experimental methodology involving system architecture design, lightweight Edge AI model development, prototype implementation, and performance evaluation under realistic operating conditions. Experimental results demonstrate that the proposed edge-based CPS significantly reduces end-to-end latency and energy consumption while maintaining acceptable inference accuracy compared to cloud-based processing. Furthermore, the system achieves improved communication efficiency and higher operational reliability, particularly under intermittent network connectivity. The findings highlight that embedding intelligence at the edge enables closed-loop sensing, decision-making, and actuation, which is essential for adaptive robotic control in environmental monitoring scenarios. This study contributes a system-level perspective on Edge AI–enabled CPS design and provides empirical evidence supporting the transition from cloud-centric architectures toward distributed, energy-aware, and resilient cyber-physical systems for real-time monitoring and control applications.

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.

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.

This study examines the impact of IT-driven innovation management on IT service effectiveness and competitive value creation within smart organizations. As digital transformation accelerates across industries, organizations are increasingly leveraging advanced IT solutions to enhance service delivery, responsiveness, and customer satisfaction. While traditional IT service management (ITSM) models focus on efficiency and structured processes, the integration of innovation management introduces new opportunities to improve service quality and operational agility. Through a quantitative research design, this study employs regression modeling to assess the relationship between IT-driven innovation management and two key outcomes: IT service effectiveness and competitive value creation. Data were collected from 100 technology-intensive organizations that actively integrate innovation into their IT service management processes. The results demonstrate that IT-driven innovation significantly enhances service quality, customer satisfaction, and organizational competitiveness. Furthermore, a curvilinear relationship was identified, indicating that while moderate innovation leads to improved outcomes, excessive innovation may have diminishing returns. These findings highlight the importance of balancing innovation efforts with business goals to achieve optimal performance. The study also compares innovation-driven IT service management with traditional models, illustrating how innovation fosters agility, responsiveness, and long-term value creation. The implications for smart organizations are clear: integrating innovation into IT service management is essential for maintaining a competitive edge in the rapidly evolving digital landscape. Future research should explore the long-term impact of innovation management on organizational sustainability and growth, considering external factors such as market volatility and technological disruptions.

In the context of both public organizations and Small and Medium Enterprises (SMEs), inefficient business processes remain a significant challenge. Fragmented information systems often hinder the optimization of these processes, leading to slower decision-making, redundant efforts, and increased operational costs. This study aims to analyze and optimize business processes by utilizing integrated information systems (IIS), providing a comparative analysis between the two sectors. The theoretical framework explores key theories such as Business Process Management (BPM) and the integration of information systems for process optimization. Previous studies highlight the differences in how IIS implementation impacts the public and SME sectors, noting challenges such as data silos, legacy systems, and resistance to change. A case study analysis methodology was employed to assess the effectiveness of IIS across both sectors. Business Process Modeling (BPMN) was used to visualize business processes before and after optimization, and process performance was measured through key metrics such as time reduction, error rates, and cost efficiency. The results show that IIS integration improved business process efficiency by an average of 28%, with reductions in redundancy and faster decision cycles observed in both sectors. Public organizations benefited from enhanced service delivery and better resource management, while SMEs gained competitive advantages through streamlined operations and increased responsiveness to market demands. The comparison reveals that integrated systems had a greater operational impact than traditional isolated process reengineering methods. Public organizations faced more regulatory and governance challenges, while SMEs leveraged their flexibility for faster integration. Recommendations for both sectors include focusing on overcoming barriers such as resistance to change and investing in system modernization. Future research should explore the long-term effects of IIS integration and further sector-specific comparisons.

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 student aims to determine how BPNT contributes community in Sipatana District, Gorontalo City. Method used is qualitative findings show that the implementation of BPNT in Sipatana District, particularly in Molosipat U and Tanggikiki sub-districts, has been carried out in accordance with the statutory regulations of 2019 regarding the indicators of power distribution and actor strategies, without any personal intervention in determining beneficiary eligibility. Regarding the characteristics of the implementing institutions, coordination among agencies from the district level to RT/RW has run well and has been conducted transparently and participatively to ensure that the assistance is well-targeted. However, on the indicators of implementer compliance and responsiveness, several obstacles are still found such as delays in disbursement, a lack of direct socialization to the community, and slow responses from the sub-district office in handling complaints from beneficiary families (KPM). These conditions lead to a lack of optimal understanding among beneficiaries regarding the mechanism of aid distribution. Additionally, the impact of BPNT on improving beneficiary welfare remains consumptive in nature and has not fully encouraged economic independence among poor households. Therefore, improvements in service effectiveness, two-way communication, and periodic evaluation are required to enhance BPNT’s contribution in reducing poverty rates and achieving sustainable community welfare.

This study examines the price elasticity of fresh cow’s milk on the demand for raw materials at Anisa Yoghurt Company using a demand theory approach. Milk is the main input in yoghurt production, making price fluctuations potentially influential on production decisions. The objective of this research is to analyze the responsiveness of raw milk demand to price changes and to identify the elasticity characteristics of milk demand in a small-scale food processing business. This study employs a quantitative case study method using primary data collected through weekly observations of milk prices and quantities purchased over a three-month period, from September to November. The analysis applies the midpoint elasticity formula to measure price elasticity of demand. The findings indicate that the demand for raw milk is consistently inelastic across the observed periods, as shown by elasticity values with absolute magnitudes less than one. Both price decreases and increases result in relatively small changes in the quantity demanded, indicating low sensitivity of demand to price fluctuations. These results suggest that raw milk is an essential production input, and purchasing decisions are driven more by production needs than by short-term price changes. The study implies that yoghurt producers should prioritize supply stability and production efficiency rather than adjusting purchase volumes in response to minor price changes. This research contributes empirical evidence on demand elasticity in dairy-based agro-industries, particularly at the small enterprise level.

Non-Cash Food Assistance (BPNT) is a government assistance program aimed at poor or underprivileged communities, distributed monthly through electronic accounts and used specifically to purchase basic necessities at designated E-Warong stores. However, in reality, the implementation of the BPNT program in the field still faces comprehensive challenges, such as issues related to targeting inaccuracy and the quality of food obtained by KPM not always meeting standards. The purpose of this study is to explore the evaluation of the Non-Cash Food Assistance (BPNT) program policy through a Systematic Literature Review (SLR) approach, so that researchers can trace various empirical findings regarding the implementation of the Non-Cash Food Assistance program policy in several regions. The policy evaluation model used is William N Dunn's model, which includes six indicators, namely effectiveness, efficiency, adequacy, equity, responsiveness, and accuracy. The results of this study are expected to provide a comprehensive and in-depth picture of the phenomenon being studied in an objective and systematic manner, and can be used as a reference for government agencies in evaluating and optimizing the implementation of the BPNT program policy so that it becomes a more effective and sustainable social assistance program.

Badan Perencanaan Pembangunan Riset dan Inovasi Daerah Probolinggo City utilizes the Regional Asset Information Sistem (SIASAD) to record and report Regional Property (BMD) in real time. However, there is a discrepancy between the percentage of Regional Government Financial Reports (LKPD) that comply with regulations, which is 100%, and the percentage of BMD data validity, which fluctuates between 86.21% in 2021 and 82.14% in 2024, indicating that the system is not optimal and there is inconsistency in BMD data. This study aims to evaluate the implementation of SIASAD in BMD management at BAPPERIDA Probolinggo City, based on the principles of Good Governance. The research method applied is qualitative with a case study approach involving data collection techniques such as interviews, observations, and document studies. The results of the study reveal that SIASAD supports the application of Good Governance through the principles of participation, consensus orientation, accountability, transparency, responsiveness, effectiveness and efficiency, fairness and inclusiveness, and compliance with the law. From this study, it can be concluded that the implementation of SIASAD contributes significantly to transparent and accountable BMD governance in accordance with the principles of Good Governance, although improvements are still needed in terms of public accessibility.

This study examines the dynamics of Buddhist religious counseling services in North Kalimantan Province in the post-pandemic period, particularly focusing on satisfaction levels and the distribution of counselors across districts. Using a quantitative approach with descriptive and correlational designs, the study involved a population of 9 Buddhist counselors and 3,993 congregants, with 98 selected respondents. Satisfaction levels were measured using the SERVQUAL framework, which evaluates service quality through five key dimensions. Findings show an overall satisfaction score of 3.65 (out of 5), categorized as “satisfied.” The highest rating was in the assurance dimension, reflecting public trust in counselor competence. However, empathy and responsiveness dimensions scored lower, especially in regions with few or no assigned counselors. A Pearson correlation analysis yielded a weak positive relationship (r = 0.214) between counselor-to-congregant ratios and satisfaction scores, emphasizing that equitable distribution is more crucial than sheer numbers. This research underscores the urgent need for needs-based distribution policies and hybrid service strategies that combine digital and in-person modalities. The results offer important policy implications, highlighting that spiritual service equity contributes to social cohesion and emotional well-being, especially in pluralistic and geographically dispersed regions.

This study aims to evaluate the public transportation service policy of Trans Jatim Bus Corridor 2, operating on the Mojokerto–Surabaya route, using the six evaluation indicators proposed by William N. Dunn: effectiveness, efficiency, adequacy, equity, responsiveness, and appropriateness. Employing a qualitative descriptive approach, data were collected through interviews, direct observations, and secondary data analysis. The findings reveal that the Trans Jatim Corridor 2 service has significantly contributed to improving accessibility and mobility for the people of East Java. In terms of effectiveness, the service meets transportation policy objectives by offering strategic routes, consistent schedules, and accessible bus stops. Efficiency is demonstrated through optimal utilization of limited fleets and operational costs, while still meeting high passenger demand. Regarding adequacy, the service is generally sufficient; however, overcrowding during peak hours indicates the need for capacity improvements. Equity is reflected in the widespread distribution of bus stops, although disparities remain in the availability of facilities and route information across several stops. The service shows high responsiveness through quick handling of passenger complaints via applications and social media. Additionally, service appropriateness is evident in its punctual operations supported by GPS-based monitoring and real-time information through the TRANSJATIM-AJAIB application. Overall, the evaluation shows that Trans Jatim Corridor 2 provides effective, efficient, and responsive public transport services, yet requires improvements in capacity and equitable distribution of facilities to achieve optimal service quality.

The rapidly changing and increasingly uncertain business environment presents significant challenges for micro, small, and medium enterprises (MSMEs), requiring them to adapt quickly and strategically to survive and remain competitive. This conceptual article examines the role of business models as an effective adaptation strategy for MSMEs in responding to dynamic market conditions, technological change, and shifting consumer preferences. Through a comprehensive review of various business model frameworks and dynamic capability theories, this study emphasizes that business models play a crucial role in shaping organizational flexibility and strategic responsiveness. The findings highlight that adaptable value propositions enable MSMEs to continuously align their offerings with evolving customer needs, while agile resource management allows firms to efficiently reconfigure internal and external resources. Furthermore, continuous business model innovation and renewal are identified as essential mechanisms for sustaining long-term resilience and competitiveness. The article argues that a business model should not be viewed merely as an operational or administrative tool, but rather as a core strategic mechanism that integrates strategic vision, organizational capabilities, and market orientation. By actively leveraging flexible and innovative business models, MSMEs can enhance their adaptive capacity, mitigate environmental uncertainty, and achieve sustainable competitive advantage in rapidly changing business environments.

This study aims to examine the influence of product innovation, digital marketing, and business networking on the competitiveness of small and medium-sized enterprises (SMEs), with customer engagement positioned as a mediating variable. Employing a Systematic Literature Review (SLR) approach, thirty Scopus-indexed articles published between 2020 and 2025 were analysed to synthesise theoretical and empirical insights related to SME competitiveness in contemporary digital and urban business environments. The findings indicate that product innovation, digital marketing, and business networking each play a significant role in strengthening SME competitiveness, particularly within markets characterised by rapid technological change. Customer engagement emerges as a critical mediating mechanism that connects these strategic variables to sustainable competitive advantage. It enhances the impact of innovative and digital strategies by fostering stronger emotional, behavioural, and participative interactions between SMEs and their customers. The review also highlights that SMEs adopting integrated digital management practices, such as the utilisation of human-resource information systems (HRIS) and data-driven decision-making tend to demonstrate greater adaptability, market responsiveness, and long-term performance. The study contributes theoretically by integrating resource-based and dynamic capability perspectives, offering a holistic understanding of how digital and relational capabilities interact to elevate competitiveness. Practically, the findings provide strategic guidance for policymakers, SME managers, and practitioners in designing innovation-oriented and digitally enabled initiatives that support sustainable SME growth in the digital era.

Growing life expectancy continues to shift global demographic patterns and significantly increase the proportion of older adults, thereby creating an urgent need for innovative programs that promote wellbeing, maintain functional capacity, and encourage meaningful social participation. This community service initiative aimed to strengthen both motor and cognitive function among older adults through structured and interactive board game activities designed to stimulate thinking, coordination, and social interaction. The program employed a mixed descriptive approach, utilizing interviews, direct observation, and brief assessments conducted before and after the intervention period. Cognitive status was measured using the Mini Mental State Examination (MMSE), while muscle strength was assessed through Manual Muscle Testing (MMT) to capture changes in physical performance. Quantitative analysis revealed no statistically significant differences between pre-test and post-test scores (p > 0.05). Nevertheless, qualitative findings demonstrated meaningful positive changes, including increased motivation, more active participation, improved emotional responsiveness, enhanced social interaction, and greater awareness of brain–body coordination among participants. These findings indicate that although short-term measurable changes were limited, board game–based activities can provide valuable psychosocial benefits. When implemented repeatedly and consistently as part of routine programs, such activities may contribute to maintaining cognitive engagement, supporting emotional wellbeing, and fostering a more active and participatory lifestyle among older adults.

The implementation of e-government is one of the local government's strategies in improving the quality of public services and realizing Good Governance. This study aims to analyze the implementation of e-government through the Tangerang LIVE Application as an effort to improve Good Governance in the Tangerang City Government. The research method used is a qualitative literature study approach through the search and analysis of various literature sources in the form of books, scientific journals, and official government documents related to e-government, the Tangerang LIVE Application, and the principles of Good Governance. This research analysis uses the Good Governance principles framework according to the United Nations Development Programme (UNDP), which includes transparency, participation, responsiveness, effectiveness and efficiency, and accountability. The results of the study indicate that the implementation of the Tangerang LIVE Application contributes positively to increasing public information disclosure, expanding public participation, accelerating government responses to public complaints, increasing the effectiveness and efficiency of public services, and strengthening the accountability of local government performance. However, there are several obstacles to achieving Good Governance through the Tangerang Live application and these obstacles become an evaluation of the Tangerang City government to innovate through e-government that supports the improvement of Good Governance in the Tangerang City Government. This study recommends strengthening digital literacy, improving institutional coordination, and sustainable system development to ensure optimal and inclusive e-government implementation.

Background: The increasing complexity of industrial production systems requires machine condition monitoring solutions that are capable of operating in real time with high accuracy and responsiveness to support predictive maintenance strategies. Conventional cloud based monitoring systems often experience limitations such as high latency and dependence on stable network connectivity, which can delay decision making processes in critical industrial operations. Objective: This study aims to design and evaluate an Industrial Internet of Things (IIoT) architecture based on edge computing to improve the efficiency of industrial sensor data processing and accelerate anomaly detection in industrial machines. Method: The research adopts an experimental approach by designing a system architecture consisting of a sensor layer, edge computing layer, and cloud layer. Industrial sensors, including vibration, temperature, and current sensors, continuously collect machine operational data, which are then processed locally at the edge node using a machine learning based anomaly detection algorithm. System testing is conducted in a simulated manufacturing environment to evaluate performance based on latency, reliability, and detection accuracy. Results: The results indicate that edge based data processing significantly reduces latency compared with cloud-based processing and enables faster responses to machine condition changes. Additionally, the implemented anomaly detection algorithm achieves high accuracy in identifying abnormal sensor data patterns.

Arabic grammar (nahwu) instruction has long been dominated by rule-based approaches that emphasize memorization and formal analysis, often resulting in rigid learning structures and limited responsiveness to learners’ cognitive diversity. While such approaches play an important role in preserving grammatical accuracy, they frequently overlook individual learning trajectories, cognitive readiness, and adaptive instructional needs. In the era of artificial intelligence (AI), language education is increasingly shaped by adaptive learning systems that personalize content, pacing, and instructional strategies based on learners’ profiles. This study aims to reconceptualize Arabic grammar instruction by proposing a conceptual framework that integrates traditional nahwu principles with adaptive learning systems informed by AI. Using a qualitative conceptual analysis, this paper synthesizes classical Arabic grammar pedagogy, contemporary theories of adaptive learning, and recent developments in AI-supported language instruction. The proposed framework highlights key components, including learner profiling, cognitive-level alignment, hierarchical nahwu content structuring, and AI-assisted scaffolding mechanisms. The findings suggest that adaptive learning systems offer significant pedagogical potential to transform nahwu instruction from a static, rule-centered model into a flexible, learner-centered process. This reconceptualization is expected to enhance grammatical comprehension, reduce cognitive overload, and promote learner autonomy in Arabic language education, particularly in Islamic higher education contexts. The study concludes by discussing pedagogical implications and directions for future empirical research on AI-assisted Arabic grammar learning.

This study evaluates the Cageur Jasa Health Service Program at the Tanah Tinggi Public Health Center in Tangerang City, which was developed as an innovation to expand access to basic healthcare services through home visits. The program aims to improve service quality, strengthen family independence in maintaining health, and support the achievement of the 12 indicators of the Indonesia Healthy Program with a Family Approach (PIS-PK). The evaluation applies William N. Dunn’s six policy evaluation criteria effectiveness, efficiency, adequacy, equity, responsiveness, and appropriateness supported by theoretical frameworks from public administration, public policy, and health service innovation. This research employs a qualitative descriptive method, with data collected through observation, in-depth interviews with informants, and secondary data analysis. The findings indicate that the program’s implementation has not fully achieved its intended objectives, as evidenced by declining service coverage, several PIS-PK indicators remaining below 50%, increasing disease findings, and the persistence of maternal and infant mortality cases. Limitations in resources, coordination, infrastructure, and suboptimal promotive and preventive efforts further hinder the program’s effectiveness. Overall, the study concludes that although Cageur Jasa contributes to improving healthcare access, its implementation at the Tanah Tinggi Public Health Center remains suboptimal and requires continuous improvement.