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This study aims to analyze the financial distress condition of PT Garuda Indonesia (Persero) Tbk during the period 2015–2024 using the Springate and Grover models. The research employs a quantitative descriptive approach with secondary data obtained from the company’s annual financial statements. Financial distress analysis is conducted by calculating financial ratios included in each model to describe the company’s financial condition over the observation period. The results indicate that PT Garuda Indonesia (Persero) Tbk experienced financial distress during several periods, particularly before and during the COVID-19 pandemic, which was reflected in weakened liquidity, declining profitability, and reduced efficiency in asset utilization. However, following the financial restructuring process after 2021, both the Springate and Grover models show an improvement in the company’s financial condition, indicating a transition toward a more stable non-distress status. Although the Springate and Grover models use different financial indicators and classification approaches, both are able to descriptively capture the dynamics of financial distress experienced by the company. The differences in classification results reflect the distinct focus of each model, where the Springate model is more sensitive to liquidity and operational performance, while the Grover model emphasizes asset profitability. Therefore, the combined use of both models provides a more comprehensive overview of the financial distress condition of PT Garuda Indonesia (Persero) Tbk during the research period.

This study explores the development strategies of sweet pastry Micro, Small, and Medium Enterprises (MSMEs) based on Islamic economic principles in improving the local economy in Betungan, Bengkulu City. MSMEs play a crucial role in supporting economic growth and creating employment opportunities, particularly in the culinary sector, which has experienced significant expansion in recent years. In Betungan, sweet pastry businesses have shown promising potential; however, their development is still hindered by several challenges, including limited capital, low product innovation, and less effective marketing practices. This research employs a qualitative approach with a case study method. Data were collected through observation, interviews, and documentation at Jl. Ar-Rahman, Sepakat 7, Betungan, Selebar District, Bengkulu City. The study also considers the application of Islamic business values, emphasizing ethical conduct such as honesty, fairness, accountability, and the avoidance of riba and uncertainty in transactions. The findings indicate that the sustainability and competitiveness of sweet pastry MSMEs can be enhanced through several key strategies, including continuous product innovation, improving product quality, optimizing digital marketing, and strengthening business networks. In addition, integrating Islamic principles into business operations helps build consumer trust and ensures ethical business practices. Overall, these strategies not only improve business performance but also contribute to strengthening the local economy and community welfare.

Strawberries are horticultural commodities that are highly susceptible to postharvest deterioration due to their high respiration rate, microbial activity, and oxidative degradation, resulting in a relatively short shelf life. This study aimed to evaluate the effectiveness of edible coatings in extending strawberry shelf life through a systematic literature review (SLR) approach. Literature was collected from several scientific databases using keywords related to edible coating, shelf life, and strawberry, covering publications from 2019–2026. From an initial 109 articles, a selection process based on inclusion and exclusion criteria resulted in 35 articles specifically discussing the application of edible coatings on strawberries. The synthesis results showed that all studies reported an extension of shelf life after edible coating application, although the effectiveness was influenced by the type of material, formulation, and storage conditions. Chitosan was the most widely used coating material due to its natural antimicrobial activity and excellent film-forming ability. The incorporation of bioactive compounds such as essential oils, plant extracts, and phenolic compounds was proven to enhance antifungal and antioxidant activities. In addition, nanotechnology-based systems demonstrated better preservation performance compared to conventional systems. However, methodological standardization and industrial-scale validation are still required to support commercial implementation.

Psychological well-being in the workplace and educational environment is influenced not only by policies and facilities but also by psychological approaches that touch on individuals' mental, emotional, and spiritual aspects. This study aims to explain how psychological approaches can enhance well-being and motivation. The results of the study show that integrating Islamic educational values, mindfulness, and emotional intelligence can help individuals manage stress, increase self-confidence, and strengthen the meaning of life. In addition, adjusting learning materials to the needs of students also plays a role in supporting mental health. Individual motivation can be increased through approaches that align with psychological needs, such as fulfilling basic needs, providing rewards, and supporting autonomy and social relationships. The implementation of strategies such as open communication, good leadership, and a comfortable work environment also contributes to increasing motivation and performance. Thus, the psychological approach has an important role in creating a healthy, productive, and sustainable educational and organizational environment.

Background: Automatic segmentation of the thyroid gland in ultrasonography (USG) images using deep learning requires a user-friendly interface to support diagnostic and educational processes. Purpose: This study aims to develop and implement a Graphical User Interface (GUI) that integrates a deep learning U-Net model for interactive and efficient segmentation and visualization of thyroid USG images. Method: The development method employed the Rapid Application Development (RAD) approach using MATLAB programming language. The GUI is designed to load transverse and sagittal USG images, display automatic segmentation results, and calculate thyroid gland volume based on dimensions measured automatically from the segmentation output. Testing was conducted using USG image data from 15 volunteers, and GUI functionality was evaluated using black box testing. Result: The GUI successfully displayed USG images and segmentation results with a responsive 4-panel interface; zoom, pan, and image navigation features functioned well. Automatic segmentation occurred in real-time after image input, and volume measurement results appeared automatically. Black box testing evaluation showed all GUI features operated as expected. The average Dice Similarity Coefficient (DSC) of 0.91 indicates high performance of the U-Net model in thyroid segmentation, consistent with previous findings. Statistical testing confirmed no significant difference between volume measurements using the application and manual methods (p = 0.953). Conclusion: This GUI implementation facilitates users in performing deep learning-based segmentation and visualization of thyroid USG images, improving efficiency and accuracy in thyroid volume measurement. The GUI has potential applications in clinical practice and radiology education.

This study aims to qualitatively analyze the impact of order cancellations and customer ratings on the performance, performance, and income of online motorcycle taxi (Gojek) drivers in the Slawi region. The research method used a qualitative approach with data collection techniques through in-depth interviews, observation, and documentation of a number of active drivers. The results show that the high rate of order cancellations, both from customers and the system, negatively impacts driver income stability and reduces work time efficiency. Furthermore, customer ratings play a crucial role in determining driver access to orders, incentives, and account sustainability. Drivers with low ratings tend to experience decreased performance due to limited opportunities to receive orders. On the other hand, the pressure to maintain high ratings also affects drivers' psychological state and work strategies. This study concludes that order cancellations and customer ratings are crucial factors that are interrelated in influencing the work quality and welfare of online motorcycle taxi drivers. Therefore, fairer and more transparent platform policies are needed to maintain a balance between customer satisfaction and driver protection.

Libraries play a crucial role in broadening the public's knowledge horizons by improving literacy skills. However, the reality at the Samaturu Library in Jambu Malea Village shows that manual management still dominates, leading to various administrative obstacles such as data irregularities, the risk of losing important information, and inefficiencies in tracking daily activities. This condition demands digital transformation to optimize public services at the village level comprehensively and sustainably. This research focuses on the development of a web-based library information system specifically designed to modernize administrative processes to be more systematic, fast, and organized. Built using the PHP programming language and MySQL database, this platform offers an intuitive interface for both staff and members. Its superior features include book data management, membership, activity agendas, announcements, and digitizing the borrowing and return process. Furthermore, the system is capable of automatically generating periodic reports to facilitate library performance evaluation. Based on the results of comprehensive testing using the Black Box Testing method, all system functionality was proven to operate optimally according to the required specifications. Direct user trials also showed very positive responses regarding aspects of ease of navigation and operational time efficiency. The implementation of this system is expected to improve the effectiveness of internal management, accelerate the quality of services to library users, and become a major catalyst in realizing superior digital literacy governance in rural areas

This research aims to classify students’ lifestyles using the K-Nearest Neighbors (KNN) algorithm. The dataset consists of 392 high school students obtained from Kaggle, with key attributes including study hours, social media usage, Netflix viewing duration, attendance, sleep quality, internet quality, mental health, and extracurricular activities. KNN was chosen for its simplicity in distance-based classification, measured using Euclidean Distance. The data was divided into training and testing sets, then evaluated using accuracy and a confusion matrix. The results show that KNN effectively classifies students’ lifestyles into four categories: healthy, less active, at risk, and highly at risk. This classification is expected to assist educational institutions, parents, and students in understanding lifestyle patterns and their impact on academic performance and mental well-being. Furthermore, this study emphasizes the relevance of applying machine learning in education, aligned with Islamic values concerning health, discipline, and the optimal use of time.

Heating, Ventilating, and Air Conditioning (HVAC) systems often suffer from significant energy wastage due to their inability to adapt to real-time environmental changes, leading to high operational costs. Although Proportional-Integral-Derivative (PID) controllers are widely used for their simplicity and reliability, they struggle to handle the complex dynamics of modern environments, requiring advanced optimization to enhance efficiency. This study aims to optimize PID controllers by integrating the Queen Honey Bee Migration (QHBM) algorithm to improve HVAC performance, energy efficiency, and adaptability. The research method employs an experimental approach that compares the performance of conventional PID controllers with PID controllers optimized using the QHBM algorithm under dynamic environmental conditions. The results show that the PID-QHBM system significantly outperforms the conventional PID system, achieving a rise time of 0.2649 seconds and a settling time of 1.6874 seconds with an almost negligible steady-state error of 9.4991e-08. Although it experiences a slight overshoot of 16.3810%, the system stabilizes quickly and maintains the target temperature efficiently. In contrast, the conventional PID controller exhibits slower response characteristics, with a rise time of 1.3730 seconds, a settling time of 2.5144 seconds, and a larger steady-state error of 0.0361. This study demonstrates that integrating the QHBM algorithm into PID controllers provides a more effective solution for real-time temperature control, offering substantial improvements in energy efficiency and system performance. The findings contribute to advancing intelligent HVAC control systems that can better adapt to environmental variations while minimizing operational costs.

This study aims to investigate the influence of Work Environment, Workload, and Leadership Style on Job Satisfaction among Non -Medical Employees at Daya Medika Clinic in West Jakarta. This study used a Likert-scale questionnaire and involved a sample of 43 employees using a non-probability sampling method and saturated sampling technique. The results of a multiple linear regression analysis using SPSS version 26 indicate that Work Environment has a positive and significant effect on Employee Job Satisfaction, Workload has no significant effect on Employee Job Satisfaction, while Leadership Style has a positive and significant effect on Employee Job Satisfaction. These findings provide insights for Daya Medika Clinic management in improving the quality of the work environment and implementing appropriate leadership styles to enhance employee job satisfaction. These findings have practical implications for improving employee performance and organizational effectiveness, and serve as a reference for further research in the field of human resource management.

The low thermal efficiency of Gas Power Plants (PLTG) due to exhaust gas heat loss drives the implementation of cogeneration at PLTGU Block II PT. PLN Indonesia Power UBP Semarang. This study analyzes the performance of the Gas Turbine Generator (GTG), combined cycle efficiency, and Exergy distribution using a 3-3-1 configuration. The research utilizes actual operational data from January 28, 2026, sampled at 10-minute intervals. Results indicate that cogeneration via a Heat Recovery Steam Generator (HRSG) significantly enhances plant efficiency. The GTG output ranged from 273–283 MW with an efficiency of 30.0–30.2%. Following combined cycle integration, system efficiency increased to 43.9–44.4%, a gain of approximately 14%, with a heat rate of 11,916–11,988 kJ/kWh. Exhaust heat of 665–713 MW was recovered to generate an additional 130 MW through the Steam Turbine Generator (STG). Exergy analysis reveals that the largest irreversibility occurs in the GTG combustion process (285 MW), followed by the HRSG (185 MW) and STG (49 MW).

Abstract. This study aims to determine the effect of Work-Life Imbalance on Customer Service Performance among banking employees who are also university students in Bandung City. Dual roles as employees and students have the potential to create an imbalance between work and academic life, which may affect the quality of customer service. This study employed a quantitative approach with a sample of 25 respondents consisting of active banking employees who are currently pursuing higher education. Data were collected through questionnaires and analyzed using simple linear regression with the assistance of IBM SPSS software. The results indicate that Work-Life Imbalance has a significant effect on Customer Service Performance. The coefficient of determination (R Square) value of 0.837 shows that the Work-Life Imbalance variable explains 83.7% of the variance in Customer Service Performance, while the remaining percentage is influenced by other variables outside the scope of this study. Therefore, banking companies are expected to provide appropriate support for employees who carry dual roles as workers and students.

The use of moldboard plows in agricultural land preparation often faces wear problems on the share component, leading to increased maintenance time and reduced operational efficiency. This study aims to design and analyze a modular concept for the plow share to improve maintenance and repair efficiency without compromising structural performance. The research methods include field observation, component dimension measurement, design modeling using CAD software, and structural analysis using the Finite Element Analysis  (FEA) method. In addition, maintenance ease was evaluated through a questionnaire based on a rating scale. The results show that the modular design significantly improves maintenance and repair efficiency, with an average score of 4.59 categorized as very good. Structural analysis indicates that the modular design reduces maximum stress on the moldboard and slightly decreases deformation, reflecting improved structural stiffness compared to the conventional design. However, the Safety Factor on the share component remains below the acceptable limit, indicating the need for further development. Overall, the modular design provides an effective solution to enhance maintenance efficiency while maintaining the structural performance of the moldboard plow.

This study analyzes the influence of good governance on urban development performance in Surabaya during 2019-2023 using a quantitative descriptive approach and secondary data from BPS and local government. Good governance is measured by SPBE, while development performance is measured by HDI, economic growth, and poverty. The results show improved governance with a satisfactory SPBE index and positive development trends, including increasing HDI, economic recovery after 2020, and declining poverty after the pandemic. The findings indicate that good governance positively affects development performance by improving policy effectiveness, public services, and supporting economic and social recovery.

Waste management remains a critical environmental issue due to the lack of public awareness in separating organic and inorganic waste, resulting in accumulation and environmental pollution This study aims to analyze and evaluate the development of automatic waste sorting systems based on proximity sensors with full-capacity notification using a Systematic Literature Review (SLR) approach.. The proposed system utilizes a combination of sensors, including proximity sensors for material identification and ultrasonic sensors for detecting object presence and bin capacity, integrated with a microcontroller for real-time processing. Additionally, the system is equipped with IoT-based monitoring that allows users to receive notifications when the waste bin reaches its capacity. The research method involves system design, hardware and software integration, and functional testing to evaluate system performance. The results indicate that the system is capable of sorting waste automatically with a high level of accuracy and responsiveness, while also providing real-time monitoring to support waste management operations. The implementation of this system can reduce manual intervention, increase operational efficiency, and promote better waste segregation practices. Furthermore, this study highlights the potential of integrating smart technology into environmental management systems, contributing both theoretically and practically to the development of sustainable waste management solutions.

The shaft is a crucial component in mechanical systems because it serves to transfer power and rotational motion throughout the machine. This research aims to assess the structural strength and operational performance of shafts used in a tire shredding machine through numerical simulation methods in order to achieve a safe and efficient design. The study involved several stages, including the development of shaft geometry models, the determination of boundary conditions, load application, mesh generation, and stress analysis using the finite element method. Two shaft configurations were examined: a 59 mm diameter shaft made from AISI 1045 steel and a 49 mm diameter shaft manufactured from ASTM A36 steel. The simulation results indicate that the 59 mm shaft experiences a Von Mises stress of 8.9 × 10⁻⁵ MPa, with a maximum displacement of 0 mm and a safety factor of 15. Similarly, the 49 mm shaft shows a Von Mises stress of 8.4 × 10⁻⁵ MPa, no measurable displacement, and a safety factor of 15. These findings confirm that both shaft designs are capable of safely withstanding the applied working loads. In addition, cutting system tests revealed that a 24-tooth blade achieved an efficiency of 26.9%, while a 40-tooth blade reached only 22.3%, indicating that the 24-tooth configuration provides better performance.

This study is motivated by the limited public understanding of the symbolic meaning of properties used in the Grombyang Dance of Pemalang, where most audiences merely enjoy the performance without recognizing the cultural values embedded within it. This research aims to examine and explain the symbolic meanings of the properties used in the Grombyang Dance of Pemalang as performed at Sanggar Seni Kaloka Pemalang. The method employed is a descriptive qualitative approach using semiotic analysis based on Charles Sanders Peirce, with data collection techniques including observation, interviews, and documentation. The results of the study indicate that the performance structure of the Grombyang Dance of Pemalang consists of three main parts: the opening, the core, and the closing, supported by various elements such as theme, movement, performers, makeup, costume, musical accompaniment, stage setting, and properties. The semiotic analysis reveals that the symbolic meaning of the properties can be understood through the relationship between representamen, object, and interpretant. The main property, the irus (ladle), functions as a symbol that not only represents the act of scooping Grombyang soup but also carries a belief-related meaning as a bringer of fortune in trading activities. In conclusion, the properties in the Grombyang Dance of Pemalang serve not only as aesthetic elements but also as a medium of symbolic communication that reflects cultural, social, and belief values within the community. Therefore, they are important to be preserved and more deeply understood by the public.

The implementation of Hospital Management Information Systems (HMIS) has become a strategic imperative to enhance operational efficiency amidst the ongoing global digital health transformation era. This study aims to analyze the determinants of successful HMIS implementation and its impact on service efficiency and patient outcome quality. Employing a narrative review approach with thematic synthesis of literature from PubMed, Scopus, and ScienceDirect databases between 2016-2026, the study evaluates the relationship between technology investment and organizational performance. The synthesis results indicate that while HMIS significantly reduces administrative burdens and medication errors, a "digital paradox" exists where technical efficiency may disrupt interpersonal interactions between healthcare providers and patients if systems are not user-centered. Key success factors include data interoperability (HL7/FHIR standards), human resource readiness, and governance policy support. This study concludes that a patient-centered efficiency model is the fundamental basis for ensuring technology investments yield sustainable added value within the healthcare delivery system.

This research is motivated by the issue of employee productivity at Estetiderma Clinic Bekasi, as indicated by the unmet distribution target data during the 2021–2024 period. In addition, there are indications that improvements are needed in the effectiveness of recruitment methods and employee work discipline, as reflected in the attendance data. The purpose of this study is to determine whether recruitment (X1) and work discipline (X2) have an effect on employee productivity (Y), either partially or simultaneously, at Estetiderma Clinic Bekasi. The research method used is associative quantitative research. The population and sample consist of all 130 employees of Estetiderma Clinic Bekasi. The data analysis techniques employed include multiple linear regression analysis, correlation coefficient analysis, coefficient of determination, and hypothesis testing (t-test and F-test). The results of the study show that: (1) the recruitment variable (X1) has a t-value of 9,503 > t-table 1.978 and a significance value of 0.000 < 0.05, indicating a positive and significant effect of recruitment on employee productivity; (2) the work discipline variable (X2) has a t-value of 13,154 > t-table 1.978 and a significance value of 0.000 < 0.05, indicating that work discipline has a positive and significant effect on employee productivity; and (3) the simultaneous F-test result shows an F-value of 114.347 > F-table 3.067 with a significance value of 0.000 < 0.05, which means that recruitment and work discipline simultaneously have a significant effect on employee productivity. These two variables contribute 64.3% to employee productivity, while the remaining 35.7% is influenced by other factors not included in this study.

This research aims to classify students’ lifestyles using the K-Nearest Neighbors (KNN) algorithm. The dataset consists of 392 high school students obtained from Kaggle, with key attributes including study hours, social media usage, Netflix viewing duration, attendance, sleep quality, internet quality, mental health, and extracurricular activities. KNN was chosen for its simplicity in distance-based classification, measured using Euclidean Distance. The data was divided into training and testing sets, then evaluated using accuracy and a confusion matrix. The results show that KNN effectively classifies students’ lifestyles into four categories: healthy, less active, at risk, and highly at risk. This classification is expected to assist educational institutions, parents, and students in understanding lifestyle patterns and their impact on academic performance and mental well-being. Furthermore, this study emphasizes the relevance of applying machine learning in education, aligned with Islamic values concerning health, discipline, and the optimal use of time.