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This study aims to examine the simultaneous and partial effects of the work environment and work-life balance on employee work stress at Hotel X. The research design is causal quantitative, with multiple linear regression analysis using SPSS 26.0 for Windows. The sample was obtained through purposive sampling (non-probability) of 120 respondents. The research subjects were employees working in shifts. The analysis results show that, (1) both variables simultaneously have a negative and significant effect on work stress, (2) the work environment has a negative and significant effect (sig. 0.002), and (3) work-life balance has a negative and significant effect (sig. 0.000). The work-life balance variable dominates its influence compared to the work environment, as seen from the lower significance value. These findings confirm that improving work-life balance and the work environment effectively reduces stress, especially for shift workers who are vulnerable to time imbalance. Based on the results, organizations are advised to optimize human resource management by maintaining a balance between job demands and employee conditions, as well as ensuring a proportional workload. Improvement in work-life balance can be achieved through flexible leave policies, adequate breaks between shifts, no overtime days except in emergencies, and minimizing personal time interruptions. These steps are expected to enhance employee well-being, retention, and productivity in the hospitality sector. Further research is recommended to explore different variables and methods, including comparing non-shift employees with the same variables, for more comprehensive insights.

Law Number 11 of 2012 emphasizes restorative justice, diversion, and the protection and fulfillment of children’s rights within the juvenile justice system. In addition, Law Number 22 of 2022 highlights the importance of guidance and assistance aimed at supporting the social reintegration of children in conflict with the law. However, the implementation of these legal provisions at the Class I Correctional Center (Bapas) in Banda Aceh has not been fully effective due to several challenges, including the limited number of officers, inadequate initial assistance, and constraints in reporting and inter-institutional coordination. This study aims to analyze the implementation of assistance provided to juvenile correctional clients at Bapas Class I Banda Aceh and identify factors affecting its effectiveness. The research employs an empirical juridical method with descriptive qualitative analysis based on interviews, documentation, and legal literature. The findings reveal that assistance has been provided throughout all judicial stages, including pre-adjudication, adjudication, and post-adjudication processes. These activities involve community research, assistance during diversion and court proceedings, and post-verdict guidance. Nevertheless, implementation remains suboptimal due to internal factors such as limited Community Advisors and heavy workloads, as well as external factors including insufficient family support, limited community acceptance, and weak coordination between institutions. These issues affect the effectiveness of assistance and hinder children’s successful social reintegration.

Occupational Safety and Health (K3) is an important aspect in protecting workers from potential accidents and health problems arising from work activities, including in the administrative sector, which is often considered low-risk. However, the Human Resources (HR) Department at PT Micro Madani Institute (MMI) Solo Branch still found several potential hazards and work risks that have not been optimally identified. This study aims to apply the Hazard and Operability Study (HAZOPS) and Job Safety Analysis (JSA) methods to identify and mitigate hazards and work accident risks in the HR Department's activities at PT Micro Madani Institute (MMI) Solo Branch. The research method is a qualitative study with a descriptive approach through observation and interviews. Risk analysis used the JSA and HAZOPS methods. The results of the study show that the application of the HAZOPS method in five sections of the HR Department successfully identified 53 potential hazards and risks, consisting of 12 extreme risks, 23 high risks, 15 moderate risks, and 3 low risks with the Employee Training and Development section as the section with the largest number of risks. Meanwhile, the application of the JSA method also identified 53 potential hazards and risks from 19 work activities. The dominant risks stem from non-ergonomic work postures, prolonged sitting, intensive computer use, and high workloads. This study concludes that the JSA and HAZOPS methods are effective in identifying potential occupational hazards and risks and can serve as the basis for control efforts to minimize workplace accidents and improve OHS implementation in the HR Department.

This study aims to analyze the registration of Deeds of Mortgage (APHT) that exceed the 7 (seven) day time limit in Badung Regency and the legal consequences that arise from this. The research uses empirical legal methods with a legislative, analytical, case, and legal sociology approach. Data was obtained through interviews with PPAT and the Badung Regency Land Office (BPN) as well as a study of secondary legal materials. The results of the study show that delays in APHT registration still occur both through the manual (offline) and electronic (HT-el) systems. The contributing factors include negligence or workload of PPAT, incomplete documents from the parties, administrative obstacles at the Land Office, and technical disruptions to the electronic system. Legally, delays do not invalidate APHT, but they delay the creation of mortgage rights because these rights only have legal force from the date of recording in the Land Registry. As a result, creditors do not obtain preferential rights and full legal protection before registration is carried out. PPATs who are late may be subject to administrative sanctions in accordance with official regulations. Based on the theories of utility, legal protection, and legal certainty, delays in APHT registration reduce the effectiveness of creditor protection and create potential legal uncertainty. Therefore, it is necessary to improve supervision and guidance for PPATs, as well as optimize the HT-el system to ensure legal certainty and protection in the practice of registering Mortgage Rights.

Low productivity and high sick leave in the weaving division of PT XYZ in Yogyakarta are caused by excessive physical and mental workload on Shuttle Loom Unit 2 operators. The productivity of the weaving division of PT XYZ was recorded at only 61.96% (target 75%) with sick leave of 4.17%, indicating operator fatigue. This study measured physical workload using the Cardiovascular Load (CVL) method based on heart rate and mental workload using NASA-TLX, and analyzed the correlation with age and length of service. The results showed a moderate physical workload category (40% light CVL <30, 60% moderate 30-60) at a temperature of 30.5°C, and high-very high mental workload (45% high 50-79, 55% very high ≥80, average EF 79.3) due to strict quality targets (0.5% defects). There is a correlation between CVL and NASA-TLX with age. Recommendations include reducing the daily production target from 100 to 85-88 yards, optimizing ergonomics, and training to reduce EF to 65 and defects to 0.3, to increase effective productivity.

The most valuable asset of a company is its employees due to their performance. The performance of PT. XYZ in recent times has tended to decline due to the heavy workload on Group A non-organic employees, which has resulted in reduced employee productivity. This study aims to determine the workload value and the level of fatigue experienced by Group A non-organic employees at PT. XYZ using the SOFI and SDS methods. It also aims to recommend efforts to reduce the workload and stress levels for Group A non-organic employees at PT. XYZ. This study is a descriptive qualitative research using interview methods and distributing questionnaires to 18 non-organic employees of group A. The results of the study indicate that the analysis of workload (fatigue) measurement using the SOFI method obtained a physical fatigue level among non-organic employees of group A at PT. XYZ with an average total score of 4.61, which means that the employees experienced a workload (fatigue) level categorized as moderate. Meanwhile, the analysis of work stress measurement using the SDS method obtained an average total score of 14, indicating that the stress level among non-organic employees of group A at PT. XYZ falls in the moderate category.

This study aims to analyze the relationship between public policy paradoxes, healthcare service quality, access to and continuity of postnatal care, and maternal mortality in Pekalongan Regency. A mixed-methods approach with a sequential explanatory design was employed, involving 30 respondents for quantitative analysis using Spearman correlation tests and 5 key informants for in-depth interviews. The results indicate that policy paradoxes are strongly correlated with service quality and with access and continuity of care. Service quality also shows a robust correlation with access and continuity. All variables are significantly associated with maternal mortality, with access and continuity of care demonstrating the strongest correlation. Qualitative findings reveal implementation gaps in Ministry of Health Regulation No. 21 of 2021, where postnatal visits are often conducted only 2–3 times instead of the mandated four visits, with 10 out of 13 maternal deaths occurring during the postnatal period. The persistence of maternal mortality is attributed to inconsistent implementation of standard operating procedures, high workload, and socio-cultural factors. The study highlights the need to strengthen supervision, enhance human resource capacity, and promote cross-sectoral collaboration to optimize postnatal care services.

The most valuable asset of a company is its employees due to their performance. The performance of PT. XYZ in recent times has tended to decline due to the heavy workload on Group A non-organic employees, which has resulted in reduced employee productivity. This study aims to determine the workload value and the level of fatigue experienced by Group A non-organic employees at PT. XYZ using the SOFI and SDS methods. It also aims to recommend efforts to reduce the workload and stress levels for Group A non-organic employees at PT. XYZ. This study is a descriptive qualitative research using interview methods and distributing questionnaires to 18 non-organic employees of group A. The results of the study indicate that the analysis of workload (fatigue) measurement using the SOFI method obtained a physical fatigue level among non-organic employees of group A at PT. XYZ with an average total score of 4.61, which means that the employees experienced a workload (fatigue) level categorized as moderate. Meanwhile, the analysis of work stress measurement using the SDS method obtained an average total score of 14, indicating that the stress level among non-organic employees of group A at PT. XYZ falls in the moderate category.

This study presents ReflectAI, a web-based system designed to automate the creation of teaching materials tailored to students' learning styles using behavior data from a Learning Management System (LMS). Student digital activity data—such as logins, material access, forum participation, assignment submission, and quiz results—are extracted and processed using a Hierarchical Clustering algorithm to categorize students into three learning styles: visual, auditory, and kinesthetic. Based on the clustering results, the system automatically generates personalized learning modules using generative AI (ChatGPT API), aligned with each student's learning preferences. Employing a data-driven system development approach, the system was tested with data from 230 students in a mathematics course. The results show diverse learning style distributions and relevant, tailored content generation. ReflectAI is designed to reduce teachers’ administrative workload and enhance personalized and adaptive learning. This system contributes to educational transformation through deep, data-driven technology integration.

MMP is a metal manufacturing company engaged in casting, forging, and machining processes with a three-shift work system, including night shifts that may increase mental and physical workload due to disruptions in workers’ biological rhythms. This study aims to analyze the mental and physical workload of die casting machine operators during the night shift and to propose improvement measures using the Fault Tree Analysis (FTA) method. The study involved 23 operators, with mental workload assessed using NASA-TLX and physical workload measured using CVL. The results indicate that mental workload falls into high to very high categories, with WWL values ranging from 46.6 to 97.3, where 12 operators experienced very high mental workload. The dominant contributing dimensions were effort, physical demand, and temporal demand. Meanwhile, physical workload ranged from 19.48% to 36.36% CVL, with most operators not experiencing fatigue. Although physical workload remains within acceptable limits, the high mental workload indicates the need for improvements. FTA analysis identified key contributing factors, including work methods, work systems, ergonomics, machine conditions, and the work environment. Proposed improvements include job rotation, improvements in work methods and task distribution, adjustments to the work system, enhanced machine maintenance, and ergonomics-based workplace improvements.

Surveillance for diarrhea at the district level in Indonesia is still affected by the fragmented nature of the District Health Information System (DHIS) and Early Warning and Response System (EWARS), inconsistent reporting, patchy data interoperability, and the resulting public health delays. Although there are systems in place like the DHIS and EWARS, the persistent use of hybrid systems that combine manual and digital data entry, as well as the different skill levels of users, continues to produce issues of incompleteness, untimely reporting, and inaccurate data. The present study investigated the deficiencies in surveillance reporting of diarrhea cases, the surveillance data to determine the degree of integration and also investigated the health workers perceptions of the barriers to effective reporting. A mixed methods approach was adopted in this study where we investigated quantitatively the DHIS and routine diarrhea reports submitted for the entire year of 2023, and combined that with qualitative, in-depth interviews with the relevant surveillance officers, program managers, and district staff. The quantitative analysis indicated gaps in reporting about 55% in terms of completeness, and consistency of reporting and also significant differences were found between the manual register, DHIS, and EWARS whereby the integration of these systems was found to be low. The qualitative analysis pointed to the combination of disconnected workflows, limited cross-system interoperability, inadequate system training, excessive workloads, and weak organizational feedback, as the main barriers to effective reporting. The combination of these two datasets illustrates the fact that both system deficiencies and organizational factors are primary drivers of the reporting. Closing the gaps will require system level changes in the interoperability of reporting systems, simplified reporting workflows, training, reporting, and reporting feedback loops.

Indonesia, as a country with a high level of disaster vulnerability, faces an increased risk of communicable diseases during the emergency response phase due to disrupted sanitation, limited access to clean water, overcrowded evacuation shelters, and weakened health services. This study aims to analyze the strategic role of health workers in health education and the prevention of communicable diseases during disaster emergency response. The method used is a literature review of relevant national and international scientific articles. The findings indicate that health workers have a multidimensional role, not only as providers of curative services but also as educators, change agents, advocates, and collaborators in promotive and preventive efforts. Effective health education, participatory risk communication, strengthened epidemiological surveillance, and the implementation of Infection Prevention and Control (IPC) are key strategies to reduce the risk of communicable disease outbreaks. However, implementation in the field still faces challenges, including limited resources, cross-sectoral coordination constraints, heavy workloads, and suboptimal disaster-related policy systems and standard operating procedures (SOPs). Therefore, strengthening the capacity of health workers through training, policy support, and community-based approaches is necessary to enhance health system resilience in responding to disaster crises.

The rapid advancement of Information and Communication Technology (ICT) has accelerated the digital transformation of public services, including land administration. However, public complaint services at the Land Office of Southwest Sumba Regency still encounter challenges such as unstructured complaint procedures, manual data processing, risk of data loss, and limited public access to clear information. These issues highlight the need for an innovative and accessible complaint information system. This study aims to design and implement a chatbot-based public complaint service information system to enhance accessibility, transparency, and service effectiveness. A qualitative research method with a system development approach was applied. Data were obtained through interviews, observations, and documentation. The system was developed using a rule-based approach with a Finite State Machine (FSM) algorithm and implemented through the Typebot.io platform. The findings indicate that the chatbot provides structured, consistent, and user-friendly information, reduces manual workload, and improves public readiness before submitting complaints directly, while supporting future integration and system enhancement.

This research aims to design and build a client service website and pre-registration of cases at the KOFIPINDO Law Office as a solution to administrative problems that are still carried out manually. The system is developed using the waterfall method through the stages of needs analysis, system design, coding, testing, and maintenance. The website that was built provides features for account registration, filling in case data, uploading supporting documents, and verification by the admin so that the file is ready to be submitted to the e-Court system. In addition, the system is equipped with a case status monitoring dashboard, automatic notifications to clients, and submission history that can be accessed at any time. The results of the study show that this platform is able to improve service efficiency, minimize administrative errors, and speed up the pre-registration process of cases. The implementation of this system also helps to increase the transparency of communication between law firms and clients. Furthermore, the use of this website has the potential to reduce the administrative workload of staff, optimize the management of case data, and improve the accuracy of legal documentation. The system is also designed with the client's data security and privacy aspects in mind in accordance with the principles of digital information protection. Thus, this system can be an effective, structured, and integrated digital means to support the modernization of legal services at KOFIPINDO, improve service professionalism, and strengthen the competitiveness of law offices in the digital ecosystem.

This study aims to evaluate the implementation of Sidoarjo Regent Regulation Number 69 of 2017 concerning the Civil Servant Code of Ethics in the Family Planning Sector at the Sidoarjo Regency Women's Empowerment, Child Protection, and Family Planning Office. A qualitative approach with a case study was used to explore the implementation of the policy through interviews, observation, and documentation. The analysis was conducted using William Dunn's six policy evaluation indicators, namely effectiveness, efficiency, adequacy, equity, responsiveness, and accuracy. The results show that the policy has provided clear behavioral guidelines and is applied evenly in the work environment. However, the effectiveness and efficiency of implementation are not optimal due to disciplinary violations, weak supervision, and unstructured communication between superiors. The aspects of adequacy and accuracy are considered relevant to the needs of the organization, but have not been able to fully overcome obstacles such as high workloads and low internalization of ethical values ​​among employees. In general, this policy contributes to shaping the professionalism of civil servants, but still requires strengthening through continuous supervision and more systematic coaching. The originality of the study lies in the use of Dunn's evaluation model in the context of the implementation of the civil servant code of ethics at the regional level, as well as identifying gaps between normative policies and field practices. These findings confirm that the success of a code of ethics depends heavily on organizational communication, work culture, and consistency of oversight.

The implementation of the Health Workload Analysis (ABK Kes) method reveals both strengths and weaknesses, particularly regarding the suboptimal execution of core tasks such as filing and distributing medical records. This study aims to compare the workload of health human resources (SDMK) between primary and advanced healthcare facilities—specifically Banyudono 1 Public Health Center and Indriati Boyolali Hospital—both of which have implemented hybrid medical record systems. Using primary data collected through interviews and observations and analyzed via the ABK Kes method, the results indicate a need for 10 additional staff members in the Casemix Unit at Indriati Boyolali Hospital and 2 additional medical record practitioners at Banyudono 1 Public Health Center. The Available Working Time (WKT) at the Public Health Center was set at 75,000 based on the Minister of PAN-RB Regulation No. 1 of 2020, whereas the Hospital used real-time calculations. While the Public Health Center aligns its policies with Ministry of Health Regulation No. 19 of 2020, the Hospital adjusts its staffing needs based on the ABK Kes results. Given that this method focuses primarily on quantity, future research and development (R&D) should integrate Lean Thinking for process analysis, ABK Kes for capacity, Queueing Theory for dynamic analysis, and NASA-TLX for psychological evaluation to provide a more holistic assessment of staffing needs.

There is one problem related with source Power man that is turnover that occurred at Hospital X and is known reach more from 10%. Research aiming for analyze Job Satisfaction as an intervention in connection between compensation compensation, leadership transformational, and burden Work to turnover intention in nurses power Work contract at Hospital X. Research use approach quantitative with type explanatory. Population in study is all over Labor Nurse Contract at Hospital as many as 562 people. The sampling method used is non-probability sampling. Research data This using primary data that is done with share questionnaire in a way direct through google form with alternative answer use scale Likert. Research This use approach Structural Equation Model (SEM) with measurement model using Smart PLS program version 3.2.9. Research results This find that in a way simultaneous all over variable influential to turnover intention. In partial compensation, leadership transformational, and burden Work found own influence significant to Job Satisfaction. More carry on in a way partial satisfaction too work, compensation, leadership transformational, and burden Work own influence significant to turnover intention.

API abuse on lightweight edge gateways has intensified as microservice-based services expose many REST endpoints to heterogeneous clients. Conventional per-identity rate limiting, such as static token buckets, is frequently bypassed through distributed bots and identity rotation, while legitimate burst traffic may be rejected and degrade user experience. This study proposes Adaptive Rate Limiting with Verifiable Delay Functions (ARL-VDF), which couples a lightweight risk score with selective VDF challenges to impose a tunable sequential-computation cost on suspicious clients without forcing aggressive dropping for low-risk users. The gateway continuously derives a per-identity risk score from short-window request rate, error tendency, and identity freshness, then maps the score to a target delay bounded by  and . Evaluation uses a 600-second discrete-event simulation on a mixed workload consisting of normal clients, legitimate bursts, and distributed attackers. Compared with a static token bucket baseline, ARL-VDF maintains full success for legitimate traffic, reduces attacker throughput that passes the gateway, and keeps verification overhead within a fixed budget on the edge device. The results indicate that combining adaptive control with verifiable sequential cost can improve availability and fairness on resource-constrained edge gateways without resorting to aggressive dropping.

Real time decision making applications, such as those used in autonomous vehicles, smart cities, and industrial IoT, require fast, scalable, and accurate analytics to ensure timely responses and optimized operations. Traditional cloud-based systems face significant challenges in meeting these requirements due to high latency, limited scalability, and bottlenecks in data processing. This study explores the use of a hybrid Edge Cloud architecture to optimize End to end machine learning (ML) pipelines for real time applications. The proposed system offloads time-sensitive tasks to edge devices, while computationally intensive processes are handled by the cloud, ensuring efficient use of resources and reduced latency. Experimental results demonstrate that the hybrid model reduces inference latency by up to 70% compared to cloud-only systems, while maintaining model accuracy and increasing throughput. Additionally, the scalability of the hybrid architecture is highlighted, as it can handle large-scale data streams and adapt to varying workloads. The findings show that hybrid Edge Cloud architectures are well-suited for applications where fast decision making is critical, such as autonomous systems and real time analytics in smart cities. However, challenges remain in managing resources across edge and cloud systems, particularly in balancing computational loads and ensuring system reliability. Future research should focus on optimizing task partitioning, integrating advanced edge AI models, and exploring the use of 5G networks to enhance performance further. Overall, the study demonstrates the potential of hybrid Edge Cloud systems in overcoming the limitations of traditional cloud-based ML pipelines and provides insights into the future of real time data processing.

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.