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Pierhead casting is a critical activity in toll road infrastructure projects that requires continuous concrete supply to maintain quality and execution time. Factors influencing the smooth casting process include the regularity of truck mixer arrival intervals and the work cycle of the truck concrete pump. This study aims to analyze the effect of truck mixer intervals and truck concrete pump performance on the productivity of pierhead casting at Pierhead P37S on the Solo–Yogyakarta–NYIA Toll Road Project, Section 2 Package 2.1A. The analysis method used field observation through time study techniques to measure the cycle duration of truck mixers and the operating time of the truck concrete pump. The analysis stages included calculating cycle time, productivity, production capacity, and working duration of each equipment. The results show that the truck concrete pump achieved a productivity of 0.425 m³/minute, while the truck mixer reached 0.989 m³/minute. These values were influenced by cycle time, equipment condition, work area condition, execution method, and work volume. Based on duration analysis, the truck concrete pump required about 4.7 hours to complete the casting of 120 m³ of ready-mix concrete, while the truck mixer required 2.022 hours to support the concrete supply process.

This study aims to determine and analyze the impact of the work environment on employee job satisfaction at the Human Resources Development Agency (BPSDM) of Jambi Province. The research is motivated by the importance of a supportive work environment in creating comfort, increasing motivation, and improving employee job satisfaction, since preliminary observations found several work-environment problems such as inadequate room cooling, disrupted toilet water supply, and unstable Wi-Fi network. This study used a quantitative approach with an associative research design. The population consisted of 75 employees, all of whom were used as the sample through a saturated sampling technique. Data were collected using a four-point Likert-scale questionnaire and analyzed with validity tests, reliability tests, classical assumption tests, and simple linear regression using SPSS. The results show that the work environment has a significant impact on employee job satisfaction, evidenced by a significance value smaller than 0.05, with a coefficient of determination of 61.8 percent. This indicates that the better the work environment, both physical and non-physical, the higher the employee job satisfaction. This research is expected to serve as a consideration for the agency in improving the quality of the work environment to support employee job satisfaction and performance.

Image Quality Assessment has become an important research area in computer vision due to the increasing use of digital imaging in medical, industrial, and remote sensing applications. This study conducted a Systematic Literature Review (SLR) using articles retrieved exclusively from the Scopus database. A total of fifteen Scopus-indexed articles were selected through the PRISMA process consisting of identification, screening, eligibility, and inclusion stages. The findings indicated that convolutional neural networks, transformer architectures, and no-reference approaches dominated recent studies because of their ability to capture complex visual features and improve evaluation accuracy. The application domain strongly influenced method selection, particularly in medical imaging, industrial quality control, and remote sensing. Deep learning methods achieved high performance but required large datasets and high computational resources. Overall, recent research trends shifted from traditional image enhancement toward artificial intelligence-based quality evaluation.

VIP Driving Course is a driving course institution that focuses on safe and effective learning. This course has experienced problems in the last five months, there has been a decrease in the number of students, recorded from January to May, respectively, there were 47, 33, 29, 25, and 21 students. This indicates a customer satisfaction issue related to service quality. The purpose of this study was to identify service quality, analyze the gap value and identify service dimensions or attributes that are prioritized for improvement. The number of respondents used was 112 respondents. This study used the SERVQUAL method to measure the gap between student expectations and perceptions, and importance performance analysis to determine improvement priorities. The results showed six attributes with negative gap values ​​including comfort of facilities, clarity of material, availability of cars, responsiveness of service, clarity of information, and attention to safety, and seven attributes with positive gap values ​​including vehicle cleanliness, neatness of instructors, time discipline, fast administration, friendly service, openness to input, and orientation to student needs. SERVQUAL analysis shows 4 dimensions with negative values ​​including tangibles of -0.21, reliability of -0.32, responsiveness of -0.29, and assurance of -0.24, while the empathy dimension obtained a positive gap value of 0.06. This indicates that most services have not met student expectations. Based on the IPA analysis, there are 4 attributes in quadrant I that are the main priority for improvement, with suggestions including rearranging the waiting room, lighting, air circulation, and supporting facilities. Increasing the number of training cars, optimizing the delivery of schedule information, procedures through digital media, and increasing attention to driving safety. Improvement efforts are made to increase customer satisfaction.

Abstract. This research aims to analyze the effectiveness and reliability of production machines in the process of making public street lighting poles (PJU) at PT. XYZ The main problem faced by the company is high machine downtime so that production targets are not achieved. Therefore, a method is needed that is able to measure machine effectiveness as a whole and identify the main causes of production losses. The method applied includes Overall Equipment Effectiveness (OEE) to measure machine effectiveness based on three components, namely availability, performance and quality. The Total Productive Maintenance (TPM) approach is used to identify factors causing low effectiveness through Six Big Losses analysis. Apart from that, Mean Time To Repair (MTTR) and Mean Time Between Failure (MTBF) are calculated to determine the level of machine reliability. The data used includes machine working hours, downtime, operating time, production quantities, defective products, as well as machine damage and repair data. The analysis results are expected to show the level of machine effectiveness and identify the dominant factors causing downtime. Based on these results, improvement proposals are prepared to reduce downtime, increase machine reliability and improve production productivity Keywords: Overall Equipment Effectiveness (OEE), Total Productive Maintenance (TPM), Six Big Losses, Downtime, Efektivitas   Abstrak. Penelitian ini bertujuan untuk menganalisis efektivitas dan keandalan mesin produksi pada proses pembuatan tiang penerangan jalan umum (PJU) di PT. XYZ Permasalahan utama yang dihadapi perusahaan adalah downtime mesin yang tinggi sehingga target produksi tidak tercapai. Oleh karena itu, diperlukan metode yang mampu mengukur efektivitas mesin secara menyeluruh dan mengidentifikasi penyebab utama kerugian produksi. Metode yang diterapkan meliputi Overall Equipment Effectiveness (OEE) untuk mengukur efektivitas mesin berdasarkan tiga komponen, yaitu availability, performance, dan quality. Pendekatan Total Productive Maintenance (TPM) digunakan untuk mengidentifikasi faktor penyebab rendahnya efektivitas melalui analisis Six Big Losses. Selain itu, dilakukan perhitungan Mean Time To Repair (MTTR) dan Mean Time Between Failure (MTBF) untuk mengetahui tingkat keandalan mesin. Data yang digunakan mencakup jam kerja mesin, downtime, waktu operasi, jumlah produksi, produk cacat, serta data kerusakan dan perbaikan mesin. Hasil analisis diharapkan dapat menunjukkan tingkat efektivitas mesin dan mengidentifikasi faktor dominan penyebab downtime. Berdasarkan hasil tersebut, disusun usulan perbaikan untuk mengurangi downtime, meningkatkan keandalan mesin, dan memperbaiki produktivitas produksi Kata kunci: Overall Equipment Effectiveness (OEE), Total Productive Maintenance (TPM), Six Big Losses, Downtime Mesin, Efektivitas Mesin

In today's rapidly developing era, advances in digital technology have brought significant changes to various fields, including the music industry. Music production processes that once relied heavily on analog equipment can now be carried out digitally through various software applications, one of which is Fruity Loops Studio (FL Studio). FL Studio is a digital music production software that is relatively easy for beginners to learn and is widely used in the creation of digital music. This technology enables individuals to create, record, edit, and produce music more efficiently without requiring expensive studio equipment. Therefore, proficiency in digital music production technology has become a relevant and essential skill for professional, educational, and creative industry purposes. Training in recording, mixing, and mastering techniques using FL Studio is one approach to enhancing the competencies of youth communities engaged in music activities. One of the target groups of this program is the K-Tong Lasiana Youth Community, a community actively involved in music creation, particularly ethnic music. However, their musical works are still primarily focused on live performances and have not been widely produced in digital recording formats due to limited knowledge and skills in digital music production. As a community service initiative, this training program is designed to equip community members with fundamental knowledge and practical skills in digital music production, enabling them to create high-quality musical works and distribute them through various digital platforms so that they can reach a broader audience.

This study aims to determine the effect of assertive leadership and self-actualization on the performance of nurses at Dr. Soekardjo Regional General Hospital in Tasikmalaya. The research design used in this study is a quantitative approach using a survey method. Research subjects: All 40 nurses working in the Melati ward were included as respondents. Research data were collected through the distribution of questionnaires to all respondents. The collected data were analyzed using a series of multiple linear regression tests, along with instrument validation and hypothesis testing. The results of the data analysis yielded the regression equation Y = 0.743 + 0.482X1 + 0.521X2 + e. Furthermore, the analysis indicated that assertive leadership positively contributes to improved nursing performance. Additionally, self-actualization also plays a role in supporting performance improvement. Simultaneously, both variables exert a significant influence on nursing performance. The coefficient of determination of 68.2% indicates that 68.2% of the variation in nurses’ performance can be explained by the two independent variables—assertive leadership and self-actualization—while the remainder is influenced by other factors outside the research model. These findings suggest that strengthening a more assertive and clear leadership style and fostering nurses’ self-actualization can serve as strategies for improving the quality of nursing care.

Hot material dumping in the chemical industry is an important process stage that affects occupational safety, process stability, and product quality reliability. In manual processes, dumping activities may cause variation because they are influenced by operator condition, pouring angle, work speed, and exposure to hot materials. This study aims to analyze the consistency of the hot material dumping process and formulate a B2B strategy based on process reliability. The research method uses a descriptive-quantitative case study approach with data from 20 batches, analyzed through three indicators: dumping time, pouring flow stability, and material temperature change or ΔT. The data were primary data obtained directly through field observation, production-process documentation, and recording of process parameters; journal literature was used only as the theoretical and interpretive basis. The results show that the automated process provides more consistent performance than the manual process. The average dumping time decreased from 49.14 seconds to 30.18 seconds, the coefficient of variation for dumping time decreased from 12.44% to 1.36%, the pouring flow stability score increased from 2.55 to 4.70, and the average material ΔT decreased from 15.26°C to 8.16°C. These findings indicate that automation can improve process regularity, reduce variation between batches, and maintain material conditions in a more controlled manner. This process consistency can serve as the basis for a B2B strategy based on process reliability, emphasizing process reliability, production safety, quality consistency, and data-based evidence as key values in building industrial customer trust.

Employee performance is essential to organizational success, particularly in the service industry, where service quality depends heavily on employees’ capabilities and workplace conditions. This study examines the effects of a learning organization culture and the work environment on employee performance, with job satisfaction as a mediating variable among service sector employees in West Jakarta. A quantitative causal approach was employed using an online questionnaire distributed through purposive sampling, resulting in 210 valid respondents. Data were analyzed using Partial Least Squares–Structural Equation Modeling (PLS-SEM) with SmartPLS. The findings reveal that both a learning organization culture and a positive work environment have significant positive effects on job satisfaction. In addition, learning organization culture, work environment, and job satisfaction each positively and significantly influence employee performance. Job satisfaction also mediates the relationships between learning organization culture, work environment, and employee performance. These results suggest that organizations can improve employee performance by strengthening continuous learning practices, creating supportive working conditions, and enhancing employee satisfaction. The study contributes to the human resource management literature and provides practical guidance for organizations seeking sustainable performance through employee-centered management strategies.

Substandard housing remains a multidimensional urban problem because it intersects with structural safety, indoor environmental quality, sanitation, clean water, poverty, and the effectiveness of policy implementation. This study evaluates the implementation of the substandard housing improvement program (RTLH) in Lubuk Linggau City by integrating a technical audit of housing quality with an implementation analysis based on the variables of communication, resources, implementer disposition, and bureaucratic structure. A descriptive-evaluative mixed approach was applied through field observation, technical scoring of ten rehabilitated houses, document review, and structured interviews with regulators, field facilitators, and beneficiary households. The results show that the cumulative technical conformity index reached 3.325 out of 4.00, equivalent to 83%, and was classified as adequate housing. Structural resilience achieved the highest score at 88%, followed by space adequacy at 85%, natural lighting and ventilation at 80%, and sanitation and clean water at 75%. Five houses were classified as adequate housing, while five were classified as fairly adequate/light substandard housing. The implementation analysis indicates that clear practical communication and facilitator assistance strengthened structural quality, but limited financial resources, weak environmental-health prioritization, and administratively oriented supervision reduced sanitation and ventilation performance. The study recommends standardized septic systems, stronger post-construction technical verification, healthy-housing education, realistic unit budgets, and quality-oriented monitoring.

Road improvement projects require consistency between technical planning documents and field implementation to ensure that service quality, structural performance, construction time, and user safety are achieved. This article evaluates the conformity between planning and realization in the Pangkalan-Batas Jambi road improvement project in Rawas Ulu District, North Musi Rawas Regency. The study used a descriptive-quantitative evaluative approach based on field monitoring, project technical documents, comparative quantity analysis between contract and Contract Change Order (CCO), and identification of implementation constraints. The results showed that several work items changed during construction because initial planning data did not fully capture actual field conditions. Quantities increased for drainage excavation (+18.87%), roadbed preparation (+8.99%), aggregate class A base course (+12.51%), and AC-Base (+11.98%). Conversely, reinforced pipe culverts decreased (-58.33%), unsealed aggregate base/sirtu decreased (-43.50%), and tack/prime coat volume slightly decreased (-0.47%). The time schedule showed a minor delay of -0.13% in the first week but recovered in the second week, indicating effective field coordination. Main constraints included traffic interference, limited worker visibility, and equipment visibility. The study recommends more detailed site surveys during planning, stronger traffic management, stricter occupational safety implementation, systematic progress control, and routine post-construction maintenance to maintain road service life.

Nursing care in hospitals is still below the established standard of 80%, thus reflecting suboptimal nurse performance. This condition is thought to be influenced by factors such as rewards, workload, length of service and supervision. This study aims to analyze the relationship between rewards, workload, length of service, and supervision with nurse performance in the Inpatient Unit of Ratu Zalecha Martapura Regional Hospital. This study used a quantitative method with an observational analytical design using a cross-sectional approach. The study sample consisted of 152 nurses selected using cluster proportional random sampling technique. Data were collected using a questionnaire and analyzed using the chi-square test and multiple logistic regression. The results showed a significant relationship between rewards and nurse performance (p-value=<0.001), workload and nurse performance (p<0.001), and supervision and nurse performance (p-value=<0.001). Length of service did not show a significant relationship with nurse performance (p-value=0,968). Multivariate analysis showed that supervision was the most dominant factor related to nurse performance. Thus, compensation, workload, and supervision are related to nurse performance, while length of service is not related to nurse performance in the Inpatient Unit of Ratu Zalecha Regional Hospital, Martapura. The hospital is expected to improve supervision, workload management, and training and recognition for nurses to improve the quality of nursing services.

The quality of life and well-being of women in Indonesia can be measured through the Female Life Expectancy indicator. Data on Female Life Expectancy from 2022 to 2024 shows a nationally positive trend; however, a significant disparity persists across provinces, particularly between the Western and Eastern regions of Indonesia. The nation still faces challenges in ensuring an equitable quality of life for women, as evidenced by the national Female Life Expectancy (FLE) in 2024 at 74.21 years, which remains lower than ASEAN counterparts such as Singapore at 83.86 years. Furthermore, regional imbalances are reflected in the performance gap between D.I. Yogyakarta (77.4 years) and West Sulawesi (68.28 years). This study aims to analyze the effects of Women's Income Contribution, Access to Clean Water, the Number of Families Receiving Social Assistance, and Women's Mean Years of Schooling on Female Life Expectancy in Indonesia during the 2022–2024 period. The estimation method applied in this research is the Fixed Effect Model (FEM) via a quantitative panel data regression approach, spanning an observation area of 33 provinces (n=99). Based on the analysis, Female Life Expectancy is proven to be positively and significantly influenced by Women's Mean Years of Schooling and Access to Clean Water. These findings indicate that human resource quality and environmental conditions serve as dominant factors in driving up Female Life Expectancy. Therefore, government policy interventions should ideally focus on expanding educational access for women and ensuring the equitable distribution of clean water infrastructure.

The development of digital services by BPJS Ketenagakerjaan through the JMO (Jamsostek Mobile) application has triggered a surge in large-scale and unstructured user reviews on the Google Play Store, thereby complicating manual analysis and conventional sentiment analysis in accurately identifying specific issues. This research aims to implement the Aspect-Based Sentiment Analysis (ABSA) method to granularly evaluate JMO application reviews based on specific aspects, while simultaneously addressing class imbalance and computational efficiency issues. The proposed method combines the pretrained IndoBERT model as a contextual feature extractor, the SMOTE technique to balance the training data, and an artificial neural network (Neural Network) as the classification layer without performing full fine-tuning. The dataset used consists of 90,268 unique reviews categorized into five main aspects through keyword matching, namely General Satisfaction/Complaints, Performance & Stability, Service & Support, Feature Quality, and UI/UX, with initial lexicon-based labeling using the InSet Lexicon. The research results indicate that the proposed model successfully achieves highly optimal performance with an accuracy rate of 91.81% and a weighted F1-score of 92%. Furthermore, the implementation of SMOTE proved effective in enhancing model reliability on the minority class (negative sentiment), achieving an F1-score of 89%. The implications of this research contribute an accurate and efficient aspect-based sentiment analysis framework for developers, and serve as a strategic evaluation tool for BPJS Ketenagakerjaan in mapping specific user complaints to accelerate continuous improvements in the performance, stability, and service quality of the JMO application.

Conflict is an inevitable phenomenon in educational environments due to differences in characteristics, interests, perceptions, and goals among school members. If not managed properly, conflict can disrupt the learning process, weaken social relationships, and negatively affect educational quality. This study aims to analyze the role of collaborative conflict management in improving the quality of education in madrasahs and schools. The research employed a qualitative approach using a library research method by reviewing various books, scientific journals, and relevant literature related to conflict management and education. The findings indicate that collaborative conflict management, implemented through effective communication, deliberation, discussion, negotiation, and cooperation, can facilitate constructive and sustainable conflict resolution. Furthermore, the application of collaborative conflict management contributes to strengthening cooperation among school members, creating a harmonious and conducive learning environment, and improving teacher performance as well as student learning outcomes. School principals play a strategic role as mediators and facilitators in guiding conflict resolution processes fairly and participatively. Therefore, collaborative conflict management can serve as an effective strategy for enhancing educational quality and fostering a positive educational climate in madrasahs and schools.

This study aims to analyze the effect of homework load and extended study hours on students’ learning stress levels. The background of this research is based on increasing academic demands that may affect students’ psychological conditions. This study employs a qualitative approach with data collected through observation and interviews. The results indicate that excessive homework load and prolonged study duration significantly contribute to higher levels of learning stress. Students tend to experience physical and mental fatigue, decreased motivation, and difficulty managing time between study and rest. In addition, pressure to achieve high academic performance further exacerbates stress levels. Other factors such as lack of environmental support and less varied teaching methods also influence students’ stress. Furthermore, students often report feelings of anxiety and emotional exhaustion when academic tasks accumulate without adequate rest periods. This condition not only affects their psychological well-being but also reduces concentration and learning effectiveness in the classroom. Therefore, balanced learning load management, appropriate task distribution, and more effective and humanistic teaching strategies are needed to reduce learning stress and improve the quality of education. Schools and educators are encouraged to consider students’ cognitive capacity and mental health in designing assignments and study schedules to create a more supportive learning environment.

This study aims to analyze the implementation of quality control in the carbonated beverage filling process using an automated filler machine and to identify critical control points that influence product conformity and production efficiency. A descriptive quantitative approach was employed through production line observation, machine monitoring, and quality control documentation review. The study focused on the filling process of carbonated beverages packaged in 330 mL aluminum cans and the associated quality control activities throughout the production line. The findings show that the filling process is the key quality control stage, supported by the automated filler machine, Fill High Detector (FHD), seaming, temperature stabilization, and traceability systems to maintain product conformity. The study was limited to a descriptive evaluation of a single production line and did not include statistical process capability analysis or quantitative measurements of filling variation. Therefore, the findings primarily provide operational insights rather than statistical validation of process performance. The findings may assist beverage manufacturers in improving filling accuracy, strengthening inspection systems, and enhancing production reliability through effective quality control practices. This study provides a comprehensive overview of quality control implementation in an automated carbonated beverage filling system and highlights the integration of filling, inspection, and supporting production processes in maintaining product quality and operational efficiency.

Document-level sentiment analysis assigns a single polarity label to an entire review, often obscuring opinion diversity within multi-sentence submissions. This limitation is particularly evident in reviews of multi-service platforms, where users frequently express heterogeneous opinions toward different aspects of the platform in the same review. To address this challenge, this study proposes a sentence-level sentiment analysis framework for Indonesian Gojek app reviews collected from the Google Play Store. The proposed framework introduces a two-stage segmentation strategy that combines punctuation-aware rules with conjunction-aware splitting based on coordinating and adversative conjunctions (e.g., tapi [but], padahal [even though]) to identify opinion boundaries and decompose mixed-sentiment reviews into independently classifiable sentence units. A total of 14,730 raw reviews collected between May and July 2025 were subjected to data cleaning and quality filtering, resulting in 7,187 valid reviews that were further segmented into 14,187 sentence-level instances. Each instance was manually annotated by three annotators using a four-class labeling scheme consisting of app-positive, app-negative, app-neutral, and service categories. Sentiment-level inter-annotator agreement, computed on the subset of instances unanimously categorized as app-related by all three annotators (n = 4,384), achieved substantial agreement (Fleiss'  = 0.636). Hyperparameter optimization was conducted using Optuna with the Tree-structured Parzen Estimator (TPE) sampler across four experimental scenarios. The best performance was achieved by IndoBERTweet under Stratified K-Fold evaluation, attaining an accuracy of 0.751 and a macro F1-score of 0.729, outperforming all IndoBERT configurations. The results demonstrate the effectiveness of domain-adaptive pre-training on informal Indonesian text and highlight the value of conjunction-aware segmentation for preserving fine-grained opinion structures in mixed-sentiment reviews. These findings suggest that domain-aligned language representations provide a practical and effective solution for sentence-level sentiment analysis of Indonesian app reviews.

Agentic artificial intelligence (AI) systems capable of autonomous goal-directed behavior, multi-step planning, tool use, multi-agent coordination, and iterative self-correction represent a transition from passive clinical AI tools toward systems that can participate in complex healthcare workflows. However, empirical evidence remains fragmented across clinical decision support, patient monitoring, and administrative applications, and no systematic synthesis has evaluated which agentic principles have been technically demonstrated and which have accumulated sufficient evidence to support responsible clinical deployment. We conducted a PRISMA-informed systematic review of peer-reviewed empirical studies published between January 2025 and April 2026. Searches across five bibliographic databases and Google Scholar, supplemented by citation tracking, identified 443 unique records for screening, of which 25 met the predefined PICOS and quality appraisal criteria. Evidence was synthesized using an evidence-informed seven-principle framework derived from the integration of agentic AI, clinical AI, and healthcare governance literature. This framework provides a structured lens for examining how agentic principles are evaluated individually and in combination, enabling a deployment-readiness perspective that extends beyond capability-focused assessments alone. The evidence base was concentrated on technical capability principles, whereas human oversight, safety, compliance, and equity-related evaluation received comparatively limited attention. Most studies remained at the laboratory, benchmark, or proof-of-concept stage, and none reported demographic-stratified performance outcomes. Overall, the findings suggest a structural asymmetry in agentic healthcare AI: empirical research is advancing agentic capabilities more rapidly than it is generating evidence for the oversight, safety, equity, and governance mechanisms required for responsible clinical translation.

This study examines human resource competence in improving financial management at the Public Service Agency of Gorontalo State University, a public higher education institution that operates under a flexible financial management model while remaining accountable for public funds. The main problem addressed is how financial management personnel translate regulatory knowledge, technical skills, and professional attitudes into efficient, effective, and accountable financial governance. This study aims to analyze the competence of financial management personnel and explain its contribution to strengthening institutional financial management. A qualitative descriptive approach was employed through interviews, observation, and document analysis involving bureau leaders, financial work team officials, treasurers, and financial managers across relevant work units. The findings show that knowledge competence is reflected in personnel understanding of regulations, policies, financial systems, budgeting procedures, reporting requirements, and the linkage between budget and institutional performance. Skills competence is demonstrated through financial administration, transaction recording, document verification, use of financial information systems, reconciliation, reporting, and preparation of accountability documents. Attitudinal competence appears in professionalism, compliance, integrity, prudence, responsibility, and openness to evaluation and audit. Financial management has been directed toward performance-based planning, expenditure control, budget realization monitoring, reporting, supervision, and audit follow-up. However, challenges remain in regulatory adaptation, system integration, data quality, document timeliness, account-code accuracy, inter-unit coordination, and consistency of audit follow-up. The study concludes that strengthening human resource competence is essential for improving financial management that is efficient, effective, accountable, and performance-oriented in public university financial governance.