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Musculoskeletal Disorders (MSDs) are disorders of the skeletal muscles that can range from very mild to very painful. Repeated static loads over a long period of time can cause damage to joints, ligaments, and tendons. Musculoskeletal disorders can occur due to several factors, including occupational factors, individual factors, psychosocial factors, and environmental factors. This study aims to analyze the relationship between age, length of service, and smoking habits with musculoskeletal disorders in furniture craftsmen. This study used an observational analytical study with a cross-sectional design. The sample used a total population of 51 workers. Data collection techniques were observation and filling out the Nordic Body Map (NBM) questionnaire. Data analysis used the Somers'd. The results of the analysis showed that there was a relationship between age (p value = 0.015), length of service (p value = 0.001), and smoking habits (p value = 0.000) with the incidence of Musculoskeletal Disorders (MSDs).

The foundation of turbine machines in industrial buildings must be able to withstand static and dynamic loads caused by operational vibrations. Generally, reinforced concrete block foundations are used due to their good stability. However, under certain conditions such as limited land, decreased soil bearing capacity, and the need for structural rehabilitation, their application becomes less effective. Therefore, this study aims to analyze the use of Micropile foundations as an alternative for turbine machine foundations at Candi Baru Sugar Factory, Sidoarjo.The research method includes literature studies, soil data collection through Cone Penetration Test (CPT), machine technical data analysis, and the design and analysis of Micropile foundations. The analysis covers bearing capacity, settlement, dynamic response, pile cap design, and cost estimation.The results indicate that Micropiles with a diameter of 0.20 m, a length of 2 m, five piles, and a pile cap size of 2 m × 2 m × 4.5 m are able to safely and stably support the machine load. In addition, this system is considered more efficient in terms of construction time and implementation. Therefore, Micropile foundations are recommended as an effective and economical alternative for turbine machine foundations.

Working memory (WM) has been extensively studied as a cognitive factor influencing second language acquisition (SLA), but many studies treat it as a static, trait-like capacity. This approach provides limited insight into how WM works across different stages of development, proficiency levels, and learning contexts. This article combines theoretical and empirical research on working memory in SLA from a dynamic and developmental perspective, analyzing how the influence of WM varies over time and interacts with other cognitive and contextual factors. Referencing Baddeley's multicomponent model, complex dynamic systems theory, and longitudinal research, this article examines evidence regarding the role of WM in various language domains, including vocabulary learning, grammar processing, and language production. It also investigates how WM works differently at various proficiency levels and developmental periods, from childhood to adulthood. Evidence suggests that WM plays a very strong role in the early stages of learning when processing is effortful and controlled, but becomes less central as linguistic knowledge becomes automated. The relationship between WM and SLA appears to be bidirectional, with sustained language learning contributing to the development of specific WM components, particularly executive control. The influence of WM varies significantly based on task characteristics, teaching context, and learner profiles. Understanding WM as a dynamic resource rather than a fixed constraint has important pedagogical implications. Instructions that manage cognitive load, provide support, and encourage metacognitive awareness can help learners with diverse cognitive profiles. A developmental approach in WM research requires longitudinal designs and task-aligned methodologies to capture changes over time, thereby advancing theory and practice in SLA.

MSMEs can play a significant role in bolstering a community's economy, with their growth highly dependent on workforce performance. Effective leadership and appropriate incentives significantly enhance employee productivity, motivation, and engagement. The purpose of this study is to ascertain how employee performance in MSMEs in the Bantar Gebang market is impacted by knowledge-oriented leadership and incentives. 135 employees of MSMEs in the Bantar Gebang market were given paper questionnaires to complete in order to gather data. Validity and reliability tests were performed using SPSS version 27 for data analysis in this study. CFA with KMO, Anti-Image, and Factor Loading was used for the validity test; Kolmogrov-Smirnov was used for the normalcy test; multiple linear regression and t-tests were used for hypothesis testing. The findings supported hypothesis 1 by demonstrating that knowledge-oriented leadership significantly and favorably affected worker performance. Additionally, the data supported hypothesis 2 by demonstrating that rewards significantly and favorably impacted employee performance. Employees need to be encouraged by MSMEs leaders to expand their knowledge and abilities through a variety of experiences. MSMEs must put in place extra incentive programs to show their staff how much they are valued. MSMEs owners are required to evaluate and recognize staff members who exhibit strong initiative and go above and beyond the call of duty.

This study aims to analyze how the integration of traditional knowledge and digital knowledge shapes organizational strategies in Micro, Small, and Medium Enterprises (MSMEs) in responding to an increasingly competitive business environment. A quantitative approach was employed by applying variance-based Structural Equation Modeling (SEM) using SmartPLS 3 software to 100 MSME respondents. The research model was developed by incorporating three main latent constructs, namely digital knowledge, traditional knowledge, and organizational strategy, which were measured using several indicators relevant to the MSME context. The analysis results indicate that all research instruments meet good reliability and validity criteria, with outer loading values ranging from 0.719 to 0.902, Average Variance Extracted (AVE) values above 0.64, and composite reliability exceeding 0.87. Structural model testing reveals that digital knowledge has a strong and significant effect on organizational strategy (β = 0.799), while traditional knowledge shows a very small effect (β = 0.024). The research model explains 66.4% of the variance in organizational strategy. These findings confirm that digital transformation is the primary factor in shaping competitive strategies among MSMEs, while traditional knowledge continues to serve as a foundation for local context and cultural values. Therefore, the implementation of a hybrid management approach is considered effective in assisting MSMEs in formulating more adaptive, innovative, and sustainable strategies.

The city of Singkawang has experienced rapid population growth, leading to an increase in the number of students. On 17 September 2024, the Singkawang City Transportation Agency implemented a free revitalized Student Transport service to reduce the number of traffic accidents involving students. The aim of this study is to identify service and respondent characteristics, evaluate operational management, and assess performance and user satisfaction using the IPA and CSI methods, as well as Vehicle Operating Costs (VOC). The research employs a descriptive quantitative method by analyzing descriptive statistical data. Data were obtained from field observations, interviews, and surveys of 400 student respondents (146 users and 254 non-users). The results show that the student transport operates with two vehicles serving the North and East Singkawang routes. The load factor for outbound trips is 22%–32% and for return trips is 11%–12%, with travel times of 68–85 minutes, average operating speeds of 20–22 km/hour, and circulation times of 68–85 minutes. Based on the IPA analysis, the indicators in quadrant D require socialization regarding the functions and use of the interior of the student transport. The CSI result shows a score of 99.79% (very satisfied). The annual VOC amounts to IDR 292,905,814 (East Singkawang) and IDR 282,020,390 (North Singkawang). In conclusion, this service is satisfactory but still requires socialization to enhance its attractiveness and effectiveness.

Overburden removal at Pit B did not meet the production targets for June and July 2025, which were set at 570,698.8 BCM and 400,986.56 BCM, respectively, while the actual production achieved was 507,071.66 BCM and 312,128.23 BCM. This study aims to determine the theoretical productivity of loading and hauling equipment and to identify the factors that hinder the achievement of production targets. The primary data used in this study include the cycle time of loading equipment, the cycle time of hauling equipment, bucket fill factor, and delay time. The secondary data required consist of swell factor, number of passes, bucket capacity, and available working time. The productivity of the loading equipment was 332.58 BCM/hour, while the hauling equipment achieved a productivity of 53.16 BCM/hour, with a match factor of 0.74. This indicates that the loading equipment experienced waiting time during loading operations due to the hauling equipment not operating optimally or at full capacity. The factors inhibiting the achievement of production targets include a narrow, waterlogged, and uneven working face; hard overburden material; a road grade of 16%, which exceeds the standard maximum of 12%; a curve road width of 15 m, which is less than the ideal minimum width of 19.95 m; undulating haul roads; narrow haul road width; and dusty road conditions.

The rapid development of smartphone technology today creates challenges for consumers and manufacturers in determining an objective price range based on highly varied technical specifications. This study aims to implement the Random Forest algorithm in classifying smartphone price ranges into four main categories, namely low, mid-range, high, and flagship. The research method was carried out systematically through the stages of loading a dataset of 2,000 entries, exploratory data analysis (EDA) to ensure data integrity, and model training with a training and testing data split of 80:20. The results showed that the Random Forest model achieved a significant overall accuracy rate of 89%. Based on feature importance analysis, it was found that RAM capacity was the most dominant determining factor, contributing 47% to prediction accuracy, followed by battery power and screen resolution as supporting features. These findings have strategic implications for manufacturers to prioritize memory capacity upgrades in determining product pricing in the market, as well as providing guidance for consumers in assessing the fairness of a device's price based on its technical capabilities.

Overburden stripping operations in the coal mining industry require optimal performance of loading and hauling equipment to achieve production efficiency. This study aims to evaluate the performance of loading and hauling equipment using the Match Factor method in overburden stripping operations at PT Bumi Artlantis Raya. The results indicate that the equipment combination achieved a Match Factor of 0.85, reflecting moderate compatibility with a potential efficiency improvement of 15%. The actual productivity of Excavator 4002 reached 137.02 bcm/hour (91.35% of the 150 bcm/hour target), while Excavator 4004 exceeded the target with a productivity of 195.73 bcm/hour (130.49% of the target). In contrast, dump truck productivity remained relatively low (Mercedes dump truck: 35.58 bcm/hour; Hino dump truck: 35.40 bcm/hour), primarily due to waiting time during loading and disposal activities. Statistical analysis reveals a strong negative correlation between cycle time and productivity (R² = 0.9929). The optimal cycle time to achieve a Match Factor of 0.80 is 969 seconds, corresponding to an optimal hauling distance of 5.38–6.725 km. Although mechanical availability and physical availability were high (94–100%), the use of availability and effective utilization were relatively low due to an imbalance between loading and hauling equipment. This study concludes that improving equipment coordination, increasing bucket fill factor, enhancing haul road conditions, and implementing preventive maintenance are essential to achieving more optimal operational efficiency in overburden stripping activities.

This study aims to identify the factors causing delays in the issuance of the Certificate of Pratique (COP) for foreign vessels and to review the standard procedures applicable at the Banten Health Quarantine through the role of PT. Bahari Tirta Jaya Banten Branch. The COP is a critical document certifying that a vessel has met health requirements and is permitted to have contact with the shore (berthing/stevedoring). The research method employed is field research through direct observation at the port and library research involving laws, regulations, and relevant port literature. The research findings indicate that delays in COP issuance are caused by several primary factors, including: (1) incomplete ship administrative documents, (2) quarantine procedures requiring additional inspections, (3) poor ship hygiene conditions, (4) limited human resources within the quarantine office, and (5) technical constraints in the quarantine information system. These delays have a significant impact on ship berthing schedules, the efficiency of loading and unloading processes, and potential financial losses for shipping companies. This study recommends the need for improved coordination between ship agents and Health Quarantine authorities, evaluation of procedural efficiency, and strengthening of information system resources to ensure smooth services within the Banten Port area.

This study aims to analyze the effect of berthing time performance on the loading and unloading process of dry bulk wheat on the MV Green Sapphire ship at PT. Gelora Perkasa Belawan. The research methods used in writing this paper are field research and library research methods. Berthing time performance has a significant influence on the smoothness and efficiency of the loading and unloading process of dry bulk wheat on the MV. Green Sapphire ship at PT. Gelora Perkasa Belawan. Optimal berthing time can accelerate the completion of loading and unloading activities, minimize operational costs, and increase company productivity. Supporting factors such as equipment readiness, workforce skills, and coordination with port authorities play an important role in achieving work targets. Conversely, obstacles such as bad weather, equipment damage, and dock congestion can extend berthing time and reduce efficiency. Therefore, planned operational management, routine equipment maintenance, administrative digitalization, and good coordination between related parties are needed to ensure berthing time remains effective and the loading and unloading process takes place safely, quickly, and efficiently.

Recommender systems play a critical role in shaping user decisions across digital platforms; however, the increasing complexity of recommendation algorithms has raised serious concerns regarding transparency, trust, and accountability. This study focuses on enhancing the transparency of recommender systems by integrating Explainable Artificial Intelligence (XAI) techniques within a MovieLens-based recommendation framework. The primary problem addressed is the opacity of conventional recommendation models, which limits user understanding of why certain items are recommended and may reduce trust, perceived fairness, and system acceptance. Accordingly, the main objective of this research is to design and evaluate a hybrid explainable recommender system that balances predictive accuracy with human-understandable explanations. The proposed approach combines Matrix Factorization, feature-importance-aware neural networks, and knowledge graph embeddings to construct a robust recommendation model. To enhance explainability, multiple XAI strategies are integrated, including model-agnostic methods (LIME, SHAP, and CLIME), argumentation-based explanations, and context-aware personalized explanations. A comprehensive evaluation framework is employed, incorporating algorithmic metrics (accuracy, fidelity, robustness, counterfactual consistency, and fairness) alongside human-centered evaluations measuring trust, transparency, cognitive load, and perceived usefulness. Experimental results demonstrate that the knowledge graph–enhanced hybrid model achieves superior recommendation accuracy compared to baseline approaches. Moreover, context-aware explanations consistently outperform other methods in terms of fidelity, robustness, and user-perceived transparency, while argumentation-based explanations are found to be the most persuasive. CLIME offers a strong balance between technical stability and interpretability. The findings indicate that no single explainability technique is universally optimal; instead, hybrid and adaptive explanation strategies are most effective. In conclusion, this study confirms that human-centered, context-adaptive XAI significantly improves transparency and user trust in recommender systems, highlighting explainability as a fundamental component rather than an optional enhancement.

This research is motivated by the high risk of fatigue experienced by ship crews during voyages, which directly affects occupational safety and mental well-being. Fatigue arises from long working hours, inadequate rest time, heavy workloads, and extreme environmental conditions such as high temperatures, engine noise, and vessel vibrations. On the MT. Sultan Mahmud Badaruddin II, the problem becomes more complex due to the tight work rhythm, short berthing periods, and fast, repetitive loading–unloading activities. Harsh weather conditions, short but intensive sailing distances, and limited relaxation facilities make the crew increasingly vulnerable to both physical and mental fatigue. In addition, a work culture that tends to be authoritarian and lacks communication exacerbates psychological pressure, especially when crew members find it difficult to report their fatigue to superiors. This study uses a qualitative method through direct observation and interviews with all crew members in the deck and engine departments. The aim is to analyze the influence of the work environment and work culture on fatigue levels onboard. The results show that environmental factors such as high temperatures, narrow workspaces, and vessel instability significantly affect physical fatigue. Meanwhile, mental fatigue is triggered by ineffective communication, hierarchical pressure, and an unsupportive work culture. These findings align with the perspectives of Mathis and Jackson and comply with the provisions of the STCW 2010 and MLC 2006, which emphasize the importance of regulating working hours and fatigue management. Overall, optimizing rest hours, improving the work environment, and reforming organizational culture are required to reduce fatigue risks.

Introduction:All-zirconia crowns are the strongest ceramic artificial crowns, made from zirconium, a silicate compound (ZrSiO4) and resistant to high temperatures. The advantages of zirconia include good mechanical properties, biocompatibility, and high corrosion resistance. Zirconia has disadvantages, such as a lack of aesthetic similarity to natural teeth. Methods and Results: Search for published articles on Elsevier, PubMed and Science Direct using predetermined keywords, namely crown,fracture resistance, and zirconiaThis literature review utilizes literature published between 2020 and 2025, accessible in full-text PDF format. Based on data searches using predetermined keywords, data was searched for the last five years, resulting in four selected articles. Discussion:  Fracture and loss of retention are problems that can occur in zirconia crowns. Several factors influence the fracture resistance of clinical crowns, such as the load received, the preparation results, material thickness, cement used, marginal adaptation and the zirconia content used. Conclusion: Zirconia crowns are the strongest ceramic artificial crowns. Fracture and loss of retention are problems that can occur in zirconia crowns. Several factors influence the fracture resistance of clinical crowns, such as the load received, the preparation results, marginal adaptation and the zirconia content used.

A steel truss bridge is a structure constructed from a series of interconnected steel bars. The loads received by this structure are analyzed and transferred to the steel bars that make up the structure. Factors that need to be analyzed in bridge construction include the location and surrounding environmental conditions. After identifying the type of soil and bedrock beneath the surface, the materials used must meet strength or durability test standards before the bridge can be operated. The materials used must comply with the Indonesian National Standard (SNI). In addition to the factors mentioned above, the bridge must undergo a feasibility evaluation. Among the various tests used to evaluate bridge strength, one is vibration testing. The vibration test method, when compared to the load test method, shows higher cost efficiency and does not cause damage to the structure.

This research is aimed at examining the operational strategies carried out by PT. Samudera Sarana Karunia Dumai in ensuring the smooth operation of the Mt. Meghna Trader ship at Pelindo Dumai Port. The main focus of the research is directed at the identification and assessment of the effectiveness of operational strategies which include the planning, implementation, and control stages of various activities such as loading and unloading, logistics, coordination with relevant parties at the port, and operational risk management. This research also includes consideration of external factors, including port regulations, market conditions, available infrastructure, and supply chain dynamics. In addition, this study emphasizes the importance of continuous performance evaluation to ensure that ship operations can run according to safety standards, time efficiency, and procedural accuracy. A qualitative approach with a case study design is used and reinforced by quantitative data to get a more comprehensive analytical picture. Data was obtained through in-depth interviews, direct observations in the field, review of operational documents, and surveys involving internal and external parties who play a role in supporting the operational process of ships at the port.

This study aims to determine how to optimize container loading and unloading activities at PT. Pelindo Multi Terminal Sibolga Branch. Container loading and unloading activities are one of the main activities in port operations that greatly affect the efficiency and productivity of maritime logistics. PT. Pelindo Multi Terminal Sibolga Branch as one of the port service providers has an important role in ensuring the flow of goods in the West Coast of North Sumatra. This study is to analyze and identify factors that affect container loading and unloading performance as well as optimization strategies to improve time, costs, and resource utilization. The methods used in this study include field observations, interviews with related parties, and analysis of historical data on operational activities. The results of the study indicate that the main obstacles come from limited equipment, lack of coordination between parties, and low utilization of information technology. Suggested optimization efforts include the addition of heavy equipment for unloading, increasing workforce training, and digitalizing monitoring and scheduling systems.  

This quantitative study analyzes the influence of Ship Docking Schedule (X1), Port Availability (X2), and Loading and Unloading Productivity (X3) on Vessel Waiting Time (Y) at Tanjung Intan Cilacap Port. Data were collected through questionnaires administered to 86 vessel crew respondents and analyzed using Multiple Linear Regression (SPSS v.26). The t-test results indicate that X1, X2, and X3 individually exert a positive and significant influence on Y.1 The regression model demonstrates robust predictive power, explaining 55.2% of the variance in vessel waiting time (R^2{adj}=0.552). Based on the standardized beta coefficients, the Ship Docking Schedule (X1, \beta=0,385) is identified as the most dominant factor, followed by Loading and Unloading Productivity (X3, \beta=0,302) and Port Availability (X2, \beta=0,307).1 This finding confirms that optimizing maritime logistics performance, particularly in bulk terminals facing physical constraints, requires prioritizing procedural efficiency and scheduling accuracy.

This study examines the factors affecting Ship Agency Company Performance (Y) at Tanjung Emas Port, Semarang. The focus is on four independent variables: Waiting Time Perception (X1), Loading and Unloading Productivity (X2), Document Handling (X3), and Human Resources (X4). Using a quantitative approach and multiple linear regression analysis, data were collected from 100 employees across 27 agency companies. The results indicate that all four independent variables have a positive and significant partial effect on company performance. Waiting Time Perception (X1) was identified as the most dominant factor, with a coefficient of β=0.322\beta = 0.322β=0.322 and tcount=3.152t_{count} = 3.152tcount​=3.152, suggesting that docking time efficiency (influenced by pilot services and vessel intensity) is the key determinant of agency performance. The coefficient of determination (Adjusted R2R^2R2) is 0.370, indicating that 37% of the variation in performance is explained by the model, while the remaining 63% is influenced by external factors such as weather and macro policies. This study underscores the importance of managing port time effectively and improving Human Resources competencies to enhance agency performance in congested and digitized maritime environments, offering strategic recommendations for regulators and port managers.

This study aims to analyze production performance and the factors influencing the productivity of mining operations at PT. XYZ during August 2025. The evaluation covers production achievement against the corporate work plan (RKAP) and the owner’s operational plan, equipment availability (Physical Availability), the productivity of loading and hauling units, and various types of loss time that reduce effective working hours. The results indicate that production realization reached only 65% of the RKAP target, while achieving 102% of the owner’s plan for total material. Low equipment availability, high loss time such as no hauler, wait operator, and front preparation, as well as the underperformance of 80-ton and 100-ton units, were identified as the main contributors to production deviation. Additional influencing factors include unit reassignment, suboptimal haul road conditions, and insufficient operational fleet numbers. The study recommends optimizing fleet management, enhancing preventive and predictive maintenance programs, reorganizing hauling workflows, and controlling dominant loss time sources to improve operational efficiency and production target achievement in future periods.