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Trucking peirformancei is onei of thei important factors in supporting thei smoothneiss of thei clinkeir loading proceiss at PT. Varia Usaha Bahari, Maspion Port, Greisik. In practicei, seiveiral obstacleis arei still eincounteireid, such as deilays in truck arrivals, leiss optimal veihiclei conditions, and opeirational coordination that has not beiein fully maximizeid. Theisei conditions may affeict thei smoothneiss of thei clinkeir loading proceiss. This study aims to deiteirminei thei condition of trucking peirformancei in thei clinkeir loading proceiss baseid on deiscriptivei analysis and to deiteirminei thei eiffeict of trucking peirformancei on thei clinkeir loading proceiss baseid on simplei lineiar reigreission analysis. This study useid a quantitativei meithod with deiscriptivei analysis and simplei lineiar reigreission. Thei data weirei obtaineid through queistionnaireis distributeid to reispondeints involveid in clinkeir loading activitieis. Thei reisults showeid that trucking peirformancei was in thei good cateigory, with aveiragei indicator scoreis ranging from 3.7 to 3.9. Thei higheist indicator was opeirational coordination and communication at 3.9, whilei thei loweist indicator was loading punctuality at 3.7. Thei reisults of thei simplei lineiar reigreission showeid thei eiquation Y = 249.374 + 34.930X, which meians that trucking peirformancei has a positivei eiffeict on thei clinkeir loading proceiss. Thei significancei valuei of 0.000 < 0.05 indicateis that thei eiffeict is significant. Theireiforei, thei beitteir thei trucking peirformancei, thei beitteir thei clinkeir loading proceiss.

Blast hole drilling is an initial stage that plays a critical role in determining the success of blasting activities in mining and construction operations. Drilling quality directly affects rock fragmentation, drilling equipment efficiency, drilling equipment productivity, as well as blasting safety and costs. This study aims to analyze the influence of drilling parameters on blast hole quality, including hole diameter, drilling depth, hole inclination, and the suitability of drilling patterns with respect to the planned blasting design. The research methodology involves field observations, actual measurements of drill holes, and analysis of data obtained from drilling and blasting productivity. The results show that deviations in hole depth and direction can lead to irregular distribution of blasting energy, resulting in suboptimal rock fragmentation and an increased potential for flyrock and overbreak. In addition, the selection of appropriate drilling methods and equipment based on rock mass characteristics has been proven to improve productivity and blast hole quality. Therefore, controlling drilling parameters and implementing proper operational procedures are essential to enhance the overall effectiveness and productivity of blasting activities. This study is expected to serve as a reference for the planning and evaluation of blast hole drilling activities to achieve more efficient, safe, and economical operations.

.This study aims to analyse the role of Financial Information Systems (FIS) in supporting risk management, decision-making, and organisational performance in the digital transformation era. This study employs the Systematic Literature Review (SLR) method to examine articles indexed in Scopus from 2016 to 2026. The PRISMA framework is used to ensure a systematic, transparent article selection process, resulting in the selection of 37 relevant articles for further analysis. The results of the study show that Financial Information Systems make a major contribution to improving financial transparency, operational efficiency, the quality of strategic decision-making, and organisational risk mitigation. In addition, the integration of emerging technologies such as Artificial Intelligence (AI), FinTech, big data analytics, and cloud computing further strengthens the effectiveness of financial information systems in modern organisations. This study contributes theoretically by mapping research trends and identifying research gaps, while providing practical benefits for organisations seeking to increase competitiveness through digital financial systems. For future research, it is recommended to develop a more predictive and intelligent Financial Information Systems model to address future business dynamics.

This study aims to examine the effect of working capital efficiency and leverage on profitability and its implications for firm value in manufacturing companies listed on the Indonesia Stock Exchange (IDX) during the 2020–2025 period. The post-COVID-19 pandemic condition has increased operational risks for manufacturing companies due to fluctuations in interest rates, exchange rates, cash management, inventories, and receivables. Therefore, companies are required to implement more effective financial strategies to maintain competitiveness. Profitability is positioned as an intervening variable because previous studies showed inconsistent results regarding the relationship between working capital efficiency, leverage, profitability, and firm value. This research uses a quantitative approach with path analysis to examine direct and indirect relationships among variables. The population consists of all manufacturing companies listed on the IDX, while the sample includes 45 companies selected from 270 firms using purposive sampling based on specific criteria, such as consistent listing and financial performance. The results indicate that working capital efficiency has a significant positive effect on profitability, leverage has a significant negative effect on profitability, profitability significantly increases firm value, and profitability fully mediates the effect of working capital efficiency and leverage on firm value. These findings provide theoretical and practical implications for managers and investors in financial decision-making.

This community service activity aims to improve the quality of business management at the "Dunia Unggas" egg-laying chicken farming MSME in Malang Regency through the implementation of Total Quality Management (TQM). The main problems faced by partners include an unstructured quality management system, low levels of cage cleanliness, the absence of systematic production records, and suboptimal feed management and disease control. The implementation method uses a participatory approach with stages of diagnostics, intervention planning, program implementation, and monitoring and evaluation. The intervention program focused on the preparation of Standard Operating Procedures (SOPs), improving sanitation and biosecurity, developing a production recording system, optimizing feed management, and increasing disease control capacity. The results of the activity showed improvements in aspects of operational regularity, cage cleanliness, consistency of production records, and partners' understanding of more professional business management. In addition, there was an increase in the quality and stability of egg production. Thus, the implementation of TQM through mentoring has proven effective in increasing operational efficiency and competitiveness of MSMEs in a sustainable manner.

The development of transportation technology encourages companies to improve vehicle monitoring systems to be more effective and measurable, particularly in addressing speeding violations that can increase accident risks and reduce operational efficiency. This study aims to analyze the implementation and effectiveness of using a buzzer integrated with the Teltonika FMB910 GPS module as a vehicle speed warning indicator at PT. Lacak Cipta Aktual. This research employs a qualitative descriptive method with a case study approach, where data were collected through observation, interviews, and documentation during a one-month industrial internship and analyzed using the Miles and Huberman model, including data reduction, data presentation, and conclusion drawing. The results show that the system is capable of detecting overspeed conditions and automatically activating the buzzer when the vehicle speed exceeds the predefined threshold of 80 km/h. Based on logbook data, the system achieved a success rate of 93.9% in responding to overspeed conditions. The use of a buzzer is proven effective in providing immediate warnings to drivers, thereby improving driver awareness and speed control. However, the system still has limitations, particularly its dependence on GPS signal stability and vehicle electrical conditions. Overall, this study demonstrates that the integration of GPS and a buzzer provides a simple, effective, and cost-efficient solution to enhance driving safety and fleet management efficiency.

Student dropout in higher education remains a persistent socioeconomic challenge, yet many predictive models reported in the literature are methodologically compromised by randomized cross-validation schemes that introduce temporal data leakage and artificially inflate predictive performance. This study proposes a longitudinal prescriptive learning analytics framework integrating three complementary methodological components: a Leave-One-Cohort-Out (LOCO) temporal validation protocol, a hybrid SMOTE-ENN class balancing strategy, and temporal velocity feature engineering derived from Learning Management System (LMS) behavioral trajectories. The framework was evaluated on a longitudinal dataset comprising 464,739 enrollment records and 77 features. Five predictive algorithms—XGBoost, LightGBM, CatBoost, Random Forest, and Logistic Regression—were comparatively assessed on a strictly isolated blind holdout cohort (2022), with CatBoost emerging as the champion estimator, achieving a PR-AUC of 0.8859, a Macro F1-Score of 0.9143, and the lowest Brier Score (0.0221), thereby demonstrating superior calibration and discriminative capability under severe class imbalance (93:7 ratio). Comprehensive ablation analysis revealed that temporal velocity features function not merely as additive predictors, but as a structural prerequisite enabling Synthetic Minority Oversampling Technique with Edited Nearest Neighbors (SMOTE-ENN) to generate high-quality synthetic boundary instances; removing these features reduced minority-class precision from 0.8302 to 0.6721. To operationalize predictive outputs into actionable intervention pathways, Diverse Counterfactual Explanations (DiCE) were implemented under a three-tier causal constraint architecture on 96 borderline high-risk students, generating 384 feasible intervention scenarios exclusively targeting forward-looking behavioral velocity metrics without constraint violations. Collectively, these findings advance the paradigm of prescriptive learning analytics by providing educational institutions with interpretable risk diagnostics and operationally feasible intervention guidance grounded in empirically validated behavioral and temporal dynamics.

The purpose of this study is to examine the effect of Good Corporate Governance (GCG), financial performance, and Earning Per Share (EPS) on firm value. The object of this research consists of state-owned enterprises (SOEs) listed on the Indonesia Stock Exchange during the period of 2021–2024. This study employs a quantitative approach using secondary data in the form of annual financial statements as the primary source. The sample was selected using purposive sampling based on predetermined criteria, ensuring that only companies with complete data and consistent reporting were included in the analysis. The independent variables analyzed include the audit committee, independent commissioners, institutional ownership, Return on Assets (ROA), and Earning Per Share (EPS). Multiple linear regression analysis was used to process the data in this study, allowing the researchers to examine the simultaneous and partial effects of the variables on firm value. The findings indicate that firm value is significantly influenced by financial performance, particularly ROA, highlighting the importance of operational efficiency and profitability in enhancing shareholder wealth. While certain GCG variables such as institutional ownership showed positive influence, other elements like audit committees and independent commissioners produced mixed results, suggesting that governance mechanisms may have varying effects depending on organizational context. Meanwhile, EPS demonstrated inconsistent results in relation to firm value, implying that market perceptions of earnings may not fully capture the impact on overall firm valuation. This study provides insights for policymakers, investors, and corporate managers on the relative importance of governance and financial indicators in value creation for state-owned enterprises.

This study examines the role of QRIS as a non-cash payment system in supporting the digitalization of micro, small, and medium enterprises (MSMEs) in Indonesia. The rapid growth of digital transactions has encouraged MSMEs to adopt more efficient, practical, and secure payment systems. This study aims to integrate the benefits and barriers of QRIS, map its position in the MSME digitalization process, and develop a conceptual framework for future research. A descriptive qualitative approach with a literature study design was employed, utilizing relevant academic sources related to QRIS, MSMEs, digital payments, and user behavior. Data were analyzed using content analysis by comparing, interpreting, and synthesizing findings from selected literature. The results indicate that QRIS contributes to simplifying transactions, improving operational efficiency, reducing cash dependency, and supporting MSMEs’ adaptation to digital payment trends. However, its implementation remains constrained by factors such as digital literacy, user readiness, trust, and infrastructural limitations. The study also highlights that QRIS adoption is influenced not only by technological advantages but also by perceived value and user trust. Therefore, QRIS can be positioned as a strategic instrument in accelerating the digital transformation of MSME payment systems. The findings imply the need for further empirical research to examine the direct impact of QRIS adoption on MSME performance and sustainability.

National milkfish aquaculture production in 2024 reached 792,864 tons, highlighting the strategic role of this commodity in supporting the economy of coastal communities. central java,as one of the main contributors, has significant potential for pond development, including in Ujungwatu Village, Jepara Regency. However, pond management still faces challenges regarding human resource (HR) quality and the optimal utilization of technology. This community service program aims to enhance students’ capacity through outreach and training on Internet of Things (IoT)-based milkfish pond development as an effort to strengthen HR at the Sidomaju 2 SME. Implementation methods include the stages of observation and problem identification, work program planning, WebGIS design, IoT outreach and implementation, and evaluation. The materials covered included an introduction to IoT concepts based on ESP8266, pond monitoring, milkfish feed management, and the implementation of WebGIS as a digital mapping system for the Kalingga milkfish ponds.The activity was attended by 20 students from MA NU Ujungwatu and was conducted in a participatory manner through experiential learning. The results of the activity demonstrated an increase in students’ understanding of the application of technology in milkfish farming, as well as heightened awareness of the importance of efficient and sustainable pond management. The main output of the program is the Kalingga Milkfish Pond WebGIS, which can be utilized as a digital medium for education and monitoring of pond areas. This program contributes to improving students’ technological literacy while supporting the strengthening of pond operational systems based on digital innovation.

This study aims to investigate the influence of academic qualifications, managerial capabilities, and Perceived Organizational Support (POS) on emotional exhaustion and its implications for employee productivity at Sunan Kudus Islamic Hospital. Using a quantitative approach, data were collected via a questionnaire from 138 respondents. Instrument evaluation procedures were conducted through validity and reliability tests, while hypothesis testing was analyzed using Structural Equation Modeling (SEM). The findings reveal that academic qualifications and POS have a significant negative effect on emotional exhaustion, indicating that increased intellectual competence and strong organizational support are effective in reducing staff emotional exhaustion. Conversely, managerial capabilities were found to have no significant influence on emotional exhaustion. In the context of performance, the analysis results show that academic qualifications, managerial capabilities, and POS have a partial, positive, and significant effect on work productivity. Practically, this study suggests that hospital management prioritize human capital development and the strengthening of a supportive organizational climate to mitigate emotional exhaustion while accelerating operational efficiency in a sustainable manner.

This article analyzes the nature of knowledge (al-‘ilm) from the perspective of Islamic educational philosophy amid the current wave of secularization of knowledge, which has produced a dichotomy between religious knowledge and general knowledge. This study employs a qualitative descriptive method with a literature review approach. The findings indicate that in Islamic philosophy, knowledge is not merely understood as an accumulation of empirical data, but also as light (nūr) that connects the subject and the object through a divine intermediary (wasilah ketuhanan). The sources of knowledge include revelation, reason, and sensory perception, which are operationalized through the instruments of the heart (qalb) and intellect (‘aql). This understanding affirms that knowledge possesses both intellectual and spiritual dimensions that are interrelated and inseparable. Furthermore, the implication of this conception of knowledge is the necessity of reconstructing the Islamic education curriculum in an integrative and interconnected manner to overcome the existing dichotomy of knowledge. Thus, Islamic education is expected to produce the ideal human being (insan kamil) who achieves a balance between intellectual intelligence and spiritual depth. The findings also emphasize the importance of epistemological integration in modern Islamic education systems and the strengthening of spiritual values in the learning process.

The digital transformation driven by the acceleration of Artificial Intelligence (AI) has fundamentally transformed leadership paradigms and the structure of the modern workplace. This study aims to provide an in-depth analysis of the various strategic opportunities and systemic risks arising from the integration of AI into contemporary organizational leadership practices, where technology is no longer merely a tool but a collaborative partner in managerial processes. Using a Systematic Literature Review (SLR) method on 30 reputable scientific journals with publications spanning up to 2026, this article analyzes the transition of the leader’s role from a conventional hierarchical model toward the concept of Augmented Leadership. Data analysis results indicate that AI implementation offers significant opportunities through data-driven decision-making systems with high precision, intelligent resource allocation optimization, and enhanced leadership intervention effectiveness, which has been documented to reach up to 35%. However, this transformation also brings a series of complex multidimensional risks, including algorithmic biases that could trigger inequality cascades, ethical dilemmas related to operational transparency (black box), and the potential erosion of the meaning of work for employees. The discussion in this article emphasizes that the success of this transformation depends not only on technical expertise, but also on redefining leadership competencies to prioritize emotional intelligence and ethical governance frameworks such as the CARE Framework (Control, Awareness, Responsibility, and Evaluation).

This research is motivated by the vital role of clean water services and the need to optimize operational revenue at BLUD UPT Water Supply Management in Batam City. The study aims to analyze the influence of willingness to pay, ability to pay, and payment awareness on BLUD revenue achievement. A quantitative associative approach was employed, involving a population of 29,047 customers. A sample of 100 respondents was determined using the Slovin formula, and data were analyzed via multiple linear regression using SPSS software. The results indicate that, simultaneously, all three independent variables significantly affect revenue achievement with an F-value of 56.825 and a significance of 0.000. Partially, willingness to pay (t=8.279), ability to pay (t=11.020), and payment awareness (t=10.435) also exert a significant influence. These findings imply that higher community payment behavior directly increases institutional revenue. It is recommended that BLUD improves service quality and payment socialization to ensure sustainable revenue achievement.

The acceptance sampling test of coffee cherries is an important quality control stage in Arabica coffee processing, yet operational evidence at the estate level remains limited. This study aimed to analyze the implementation of acceptance sampling for coffee cherries and to identify the proportions of normal and defective cherries as a basis for improving harvest quality. The research was conducted at an Arabica coffee estate in Situbondo by observing monthly harvest samples from April to August 2024 to classify cherry color (red, partially ripe, green, and black) and fruit density after soaking (partially empty, empty, single bean, and double bean). The results showed that the cherry composition consisted of 93.63% red, 3.54% partially ripe, 0.09% green, and 2.84% black cherries. The density test results indicated 4.30% partially empty cherries, 0.79% empty cherries, 10.27% single-bean cherries, 84.58% double-bean cherries, and 4.00% coffee berry borer-infested cherries. These findings indicate that acceptance sampling is useful for identifying harvest lots that do not meet quality standards and can serve as a basis for improving red cherry picking practices, harvest timing, and field supervision.

This research is motivated by the increasing role of Artificial Intelligence (AI) in organizational transformation and the crucial function of leadership in ensuring its successful implementation. The primary objective of this study is to analyze the relationship between leadership, AI integration, and organizational performance, as well as to identify various challenges and supporting factors in the process. This study employs a systematic literature review (SLR) method by examining 30 relevant, reputable scientific articles from the Scopus and Google Scholar databases within the 2020–2026 timeframe through selection, evaluation, and thematic synthesis processes. The results indicate that AI integration significantly contributes to improving operational efficiency, data-driven decision-making quality, and organizational innovation. However, this success heavily depends on the role of adaptive, transformational, and digitally-oriented leadership capable of steering the technological vision. Conversely, major challenges were identified, such as employee resistance, limited digital competencies, and ethical issues surrounding data privacy. This study contributes to strengthening the conceptual understanding of leadership's role as a bridge between technology and organizational performance, while offering practical implications for management in designing effective, inclusive, and sustainable digital transformation strategies.

The management of medicines and Medical Consumables (MCs) plays a crucial role in improving the quality of pharmaceutical services in hospitals. Common problems include stock imbalances, such as shortages and overstocking, which negatively affect service efficiency, increase operational costs, and raise the risk of product expiration. These issues are often caused by inadequate planning that is not based on consumption data, as well as limited knowledge of pharmacy personnel in applying appropriate inventory control methods.This community service activity aimed to improve the knowledge and skills of pharmacy staff in managing inventory using fast moving and slow moving methods based on real hospital data. The implementation method consisted of education, training, and hands-on mentoring conducted in several stages. The activity began with the analysis of medicine and medical consumables usage data from January to December 2025 at Labuang Baji Regional General Hospital, followed by training on pharmaceutical logistics management, and continued with practical exercises on classification and inventory control. Evaluation was carried out through discussions, case studies, and observation of participants’ ability to apply the methods.The results showed that 50.7% of medicines and 52.4% of medical consumables were categorized as fast moving, while the remaining items were classified as slow moving. After the intervention, there was a significant improvement in participants’ understanding of inventory classification, stock turnover analysis, and data-based planning. Participants were also able to identify items at risk of stock-outs and overstocking, enabling more appropriate control measures.This activity had a positive impact on the efficiency of pharmaceutical inventory management, reduced the risk of stock-outs and overstocking, and supported the improvement of healthcare service quality. Therefore, the fast moving and slow moving methods can be considered effective and applicable approaches for data-driven pharmaceutical inventory management in hospital settings

This study aims to design and develop a web-based sales information system for a goat farming business at Herman Farm using the Rapid Application Development (RAD) method. The identified problems include manual transaction recording, stock management, and sales reporting processes, which are inefficient, prone to errors, and unable to provide real-time data access. The RAD method is selected due to its ability to accelerate system development through an iterative approach and active user involvement in each stage, including requirements planning, system design, construction, and implementation. Data collection techniques include observation, interviews, and literature studies. The developed system provides features for managing goat data, sales transactions, customer management, and integrated sales reporting within a web-based platform. The results show that the system improves efficiency in data management and transaction processes, while producing more accurate, structured, and accessible reports. Therefore, this system can assist Herman Farm in optimizing its sales operations and expanding its online marketing reach.

The oil and gas industry requires efficient initial processing to separate reservoir fluids into oil, gas, and water phases. The Separator Unit is the main facility that plays a vital role in the surface facility production stage. This study aims to evaluate the type of separator used, identify control components, and understand the working principles and operational procedures of separators in the Main Production Facility (MPF) area. The methodology used is direct observation and literature studies during the implementation of practical work in July 2024 at PT. Citic Seram Energy Limited, Seram Non Bula Block, Maluku. The observation results show that the type of separator used is a Horizontal Three Phase Separator with tag codes 03-V-001A and 03-V-001B operating alternately. The separation process is carried out based on differences in fluid density utilizing gravity, supported by internal components such as deflector plates, mist extractors, weirs, and straightening vanes. Separator operation is maintained at an operating pressure of around 55 psig to ensure optimal separation efficiency and work safety. The conclusion of this study indicates that effective separator operation requires stable pressure and temperature control as well as routine maintenance to prevent sediment buildup and maintain product quality.

The ICU is one of the largest clinical cost centers in hospitals due to its high demand for human resources, medical equipment, and operational costs. This situation emphasizes that intensive care unit efficiency is a multidimensional issue that cannot be assessed solely from a single aspect. This study aims to analyze the efficiency of the intensive care unit at Ciremai Hospital, Cirebon City, using the Data Envelopment Analysis (DEA) model to determine resource optimization. Analytical quantitative study with a cross-sectional design. The population in this study consisted of personnel in the ICU of Ciremai Hospital from 2023 to 2025, with total sampling applied. The input variables included the number of physicians, nurses, beds, monitors, and ventilators, while the output variables consisted of BOR, LOS, and recovered patients. The ICU input variables remained stable during the study period, while output variables fluctuated with a declining trend in BOR and LOS. The results of the Data Envelopment Analysis (DEA) indicated that all study periods achieved an efficiency score of 1.00 (efficient), with a slack value of 0.00 across all input variables.