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The ability to read the Qur’an is a fundamental competence in Islamic education. However, many children still face difficulties in reading the Qur’an accurately and fluently in accordance with tajwid rules. This community service program (Pengabdian kepada Masyarakat/PKM) aimed to improve Qur’anic reading skills of students at Asy-Syakirin Qur’anic Learning Center (TPQ) in Nibung Village, Kapuas Hulu Regency, West Kalimantan. The program employed a Participatory Action Research (PAR) approach, actively involving teachers and students in all stages of the activities. The implementation consisted of planning, action, observation, and reflection stages. During the planning phase, students’ initial reading abilities were identified and grouped into basic (iqra’) and advanced (tahsin) levels, appropriate learning methods were selected, and supporting learning media were prepared. The action phase involved individual and small-group mentoring, guided Qur’an reading with direct correction of pronunciation (makharij al-huruf) and tajwid, application of memorization and dictation (imla’) techniques, and varied teaching approaches through instructor rotation. Evaluation was conducted through pre-tests and post-tests, direct observation of students’ reading performance, and assessment of participation and attendance. The results indicate a significant improvement in students’ Qur’anic reading skills, particularly in fluency, accuracy of pronunciation, and basic understanding of tajwid. This program is expected to serve as a sustainable model for improving Qur’anic literacy in Qur’anic learning institutions.

Customer churn is a strategic challenge for digital streaming platforms because it directly Impacts revenue and business sustainability. This study aims to analyze the factors influencing customer Churn and develop a churn prediction model using the Random Forest algorithm. The study uses a Quantitative approach with an explanatory design and utilizes secondary data from the Netflix Customer Churn and Engagement Dataset available on Kaggle. The dataset consists of 1,000 customer data with 16 Variables covering demographic characteristics, service usage behavior, financial condition, and customer Satisfaction level. The data was processed through preprocessing, one-hot encoding, and a 70:30 split Between training and test data. Model performance was evaluated using accuracy, precision, recall, F1 Score, and ROC-AUC metrics. The results show that the Random Forest model produces an accuracy of 53.7%, precision of 56.3%, recall of 63.6%, F1-score of 59.7%, and ROC-AUC of 0.534, indicating Moderate predictive ability and only slightly better than random classification. Feature importanceAn.evealed that user engagement levels, such as viewing duration and frequency of interactions, Were the most dominant factors influencing churn, followed by economic factors and customer satisfaction. The results of this study are expected to provide a basis for streaming platforms to design more effective Customer retention strategies.

This study aims to strengthen students’ networking competencies through the implementation of straight and cross LAN cable assembly training at SMKN 53 Jakarta. The background of this research is based on the need to enhance students’ practical skills in basic computer networking, particularly in understanding cable configurations and applying crimping techniques according to industry standards. Many students experience difficulties in differentiating wiring standards and applying correct crimping procedures, which impacts their readiness for industry practice. This research employed a practical training approach combined with demonstration and hands-on methods. The participants were students of the Computer and Network Engineering program. Data were collected through observation, performance assessment, and competency tests before and after the implementation. The findings indicate a significant improvement in students’ understanding of cable color standards (T568A and T568B), accuracy in assembling straight and cross cables, and testing results using LAN testers. Students demonstrated higher levels of technical accuracy, problem-solving skills, and work discipline after the intervention. The implementation of structured practical activities proved effective as a medium for strengthening networking competencies. The study implies that continuous practice-based learning aligned with industry standards is essential in vocational education to improve students’ technical readiness and employability in the networking field.

The rapid development of digital technology has led to an increased adoption of digital payment methods in online transaction-based businesses. However, in practice, failures and limitations in the implementation of digital payment systems still occur, potentially disrupting transaction processes and reducing customer convenience. Payment related obstacles may result in transaction cancellations and increase the risk of customer churn. This study aims to analyze the impact of failures and limitations in digital payment methods on customer churn using a classification-based approach. The data used in this research are secondary e-commerce customer data obtained from the Kaggle platform, including transaction information, payment methods, customer behavior, and historical transaction records. The research methodology consists of data preprocessing, time-based feature engineering, and classification modeling using logistic regression, decision tree, and random forest algorithms. Model performance is evaluated using accuracy, precision, recall, F1-score, and confusion matrix metrics. The results indicate that the decision tree model demonstrates superior capability in identifying churn customers compared to the other models, although it does not always achieve the highest accuracy. In addition to digital payment methods, other factors such as purchase value, transaction frequency, purchase timing patterns, and product return rates also influence customer churn. The findings highlight the importance of optimizing digital payment systems as part of customer experience enhancement strategies and customer retention efforts in online transaction–based businesses.

The increasing complexity of competition in the healthcare industry requires hospitals to adopt adaptive and strategic management practices to enhance organizational competitiveness. This study aims to analyze the role of strategic management in improving hospital competitiveness through a Systematic Literature Review (SLR) approach. A total of 41 national and international scientific articles published between 2014 and 2025 were reviewed, sourced from Scopus, Web of Science, Google Scholar, and Sinta databases, following the PRISMA guidelines for literature selection. The synthesis of findings indicates that strategic management plays a significant role in strengthening hospital competitiveness through clear strategy formulation, consistent implementation, and continuous performance evaluation. Key factors contributing to competitive advantage include strategic leadership, adaptive organizational culture, effective human resource management, utilization of information technology, and integration between strategic planning and operational processes. The results emphasize that hospitals implementing strategic management comprehensively are better equipped to respond to environmental dynamics, improve service quality, and sustain competitive advantage in the long term. This study highlights the importance of strategic management as a foundational element in modern hospital governance and provides a conceptual basis for future empirical research in healthcare management.

This study aims to analyze the influence of interest rates, exchange rates, and coffee production on the value of coffee exports in South Sulawesi. The background of this study is based on the condition of South Sulawesi coffee exports which have experienced significant fluctuations in recent years despite coffee production tending to increase. This study uses a quantitative approach with time series data for the period 2009-2023 sourced from the World Bank, International Monetary Fund and the Directorate General of Plantations, the Food Crops, Horticulture and Plantation Service of South Sulawesi Province. Data analysis was conducted using multiple linear regression through the EViews 12 application with the classical assumption test as a model prerequisite. The results show that partially interest rates have a significant effect on coffee exports, while exchange rates and coffee production do not have a significant effect. Simultaneously, the three independent variables do not have a significant effect on the value of coffee exports. This finding indicates that external factors, especially interest rates, are more dominant in determining the performance of South Sulawesi coffee exports than internal factors of production and exchange rates.

This study examines the influence of Work Motivation, Leadership Style, Work Commitment, and Teamwork on the Work Performance of employees at the Directorate of Security (Ditpam) of the Batam Business Agency (BP Batam). A quantitative approach with an associative research design was employed. The population consisted of all Ditpam BP Batam employees, totaling 94 respondents, selected using a purposive sampling technique. Data were collected through questionnaires that had been tested for validity and reliability. The collected data were analyzed using multiple linear regression, along with simultaneous testing (F-test) and partial testing (t-test). The results indicate that simultaneously, Work Motivation, Leadership Style, Work Commitment, and Teamwork have a significant effect on employee Work Performance, as shown by an F-count of 12.455, which exceeds the F-table value of 2.47, and a significance value of 0.001 (< 0.05). Partially, each independent variable also demonstrated a significant influence on work performance, with t-count values exceeding the critical t-table value. These findings suggest that higher motivation, effective leadership, strong work commitment, and solid teamwork play an important role in improving employee performance. Therefore, it is recommended that the management of the BP Batam Security Directorate continuously enhance employee motivation, apply participatory leadership practices, strengthen organizational commitment, and foster harmonious teamwork to improve overall work performance.

The shoe manufacturing industry demands a planned, integrated, and consistent production system in maintaining product quality. One of the crucial stages is the gluing process between the outsole (rubber) and the midsole (phylon), which determines the adhesive strength, comfort, and durability of the shoe. This study aims to analyze the implementation of internship activities in a series of gluing processes in the Stockfit Department of PT X. The research method uses a qualitative descriptive approach with data collection techniques through direct observation, involvement in production activities, and systematic field recording during the internship period. The analysis was carried out by linking the field findings with the operations management theory of Heizer and Render, the Crosby concept of quality management, and the principles of continuous improvement from Deming and Imai. The results of the study show that the gluing process has been systematically arranged, starting from material adjustment, primary application, the use of two types of glue, the rubber cutting process, to the final pasting. However, problems were found such as dependency between processes, inconsistency in glue thickness, as well as the influence of machine conditions and operator skills. These problems have the potential to reduce production efficiency and the quality of the final product. Therefore, it is necessary to strengthen process control and apply the principle of continuous improvement to improve overall production performance.

International student enrollment is a critical driver of financial sustainability for Higher Education Institutions (HEIs). While advanced forecasting is standard in the corporate sector, its application in educational planning remains limited. This study addresses this gap by comparing the predictive performance of ARIMA, Facebook Prophet, and Long Short-Term Memory (LSTM) models. Using a publicly available annual dataset from a US-based institution (2000–2022), the analysis employed a strategic partition training on 2000–2017 and testing on 2018–2019 to validate models on stable, pre-pandemic data. Empirical results revealed that the statistical ARIMA (2,1,0) model demonstrated superior accuracy, achieving a Mean Absolute Percentage Error (MAPE) of 1.26%. Conversely, Prophet (11.81%) and LSTM (13.84%) struggled with the limited sample size, failing to generalize effectively compared to the linear approach. The findings suggest that for annual enrollment trends, parsimonious statistical models outperform complex deep learning architectures, providing administrators with a robust, accessible framework for data-driven strategic decision-making.

This study aims to analyze the implementation of human resource management (HRM) audits in motivating employee performance at CV Cipta Alignment Constructions (CV.CLC). HRM audits serve as an evaluative and strategic tool in assessing the effectiveness of personnel functions such as recruitment, training, career development, and reward systems. The study used a qualitative approach with a case study method through interviews, observation, and documentation. The results show that HRM audits have a positive effect on employee motivation and performance by increasing work morale, placing employees according to competencies, and reducing turnover. Based on Resource-Based Theory (Barney, 1991), HRM audits are valuable and difficult-to-imitate strategic resources, thus supporting a company's competitive advantage. These findings emphasize the importance of implementing HRM audits continuously as part of a management strategy to improve organizational effectiveness. The implications of this study provide recommendations for companies to integrate HRM audits into strategic planning to achieve optimal and sustainable performance. In addition, this study also opens opportunities for further studies to strengthen the implementation of HRM audits in different sectors and company scales.

Digital images often experience noise disturbances that can reduce visual quality and interfere with the image analysis process. One common type of noise is salt and pepper noise, especially in grayscale images, which is characterized by the random appearance of black and white dots. This study applied the Deep Convolutional Autoencoder (DCAE) method with a skip connection mechanism to eliminate salt and pepper noise in grayscale images measuring 256×256 pixels. The dataset used consists of 300 pairs of clean images and noisy images that have gone through the preprocessing stage, including normalization and data augmentation. The model was trained using an Adam optimizer with a Mean Squared Error (MSE) loss function and validated through a train-test split scheme to avoid overfitting. Model performance was evaluated using Peak Signal-to-Noise Ratio (PSNR) and Structural Similarity Index (SSIM) metrics. The test results showed that the DCAE model with skip connections was able to effectively reduce noise while maintaining the main structure of the image based on the PSNR and SSIM values obtained, and showed better performance than conventional median filters. In addition, the model was successfully implemented into a Streamlit-based application to perform the image denoising process interactively, making it easier for users to experiment and visualize results in real-time.

Background: Accurate detection of renal cysts on CT urography requires high diagnostic precision, while manual interpretation by radiologists is susceptible to inter-observer variability and potential delays in clinical decision-making. These challenges underscore the need for a reliable automated detection system to support radiological assessment. Objective: This study aims to develop and evaluate the performance of the Neo-ZasAI application based on the YOLOv8 algorithm for the automatic identification of renal cysts. Methods: Employing a Research and Development design using the ADDIE model, the study encompassed needs analysis, model design, software development, system implementation using 200 CT urography images, and diagnostic performance evaluation. Classification results generated by Neo-ZasAI were compared with radiologist readings through confusion matrix analysis and ROC–AUC assessment. Results: The findings indicate that Neo-ZasAI achieved an accuracy of 97,5%, sensitivity of 96%, specificity of 99%, positive predictive value of 98,9%, and negative predictive value of 96,1%. The ROC analysis yielded an AUC of 0.988 (p < 0.001), demonstrating excellent discriminative capability and high concordance with radiologist interpretations as the diagnostic gold standard. Conclusion: These results suggest that Neo-ZasAI is capable of performing rapid, consistent, and accurate renal cyst detection and is thus feasible for implementation as a clinical decision support system in radiology, with potential integration into PACS workflows and further development to enhance model generalizability.

State revenue holds a vital position in sustaining national development and the functioning of government, with taxation serving as the primary contributor to Indonesia’s State Budget (APBN). The substantial reliance on tax income obliges the government to manage the taxation system in an optimal, efficient, and sustainable manner. Nevertheless, the attainment of tax revenue targets in practice remains challenged by various issues, including structural, administrative, and strategic limitations. This study seeks to examine the role of strategic tax management in supporting the achievement of state revenue objectives. The research adopts a literature review approach by analyzing textbooks, national and international scholarly journals, official government publications, and relevant regulatory frameworks. The data are analyzed using a descriptive qualitative method through processes of classification, comparison, and synthesis of findings from previous studies. The findings reveal that strategic tax management has a crucial influence on enhancing state revenue performance through coherent policy formulation, flexible strategy execution, and ongoing performance assessment. The integration of information technology, the reinforcement of tax administration, and the improvement of taxpayer compliance emerge as key determinants in achieving revenue targets. Accordingly, strategic tax management constitutes a fundamental tool for ensuring fiscal resilience and promoting sustainable national development.

This study aims to: (1) describe the Arabic learning outcomes of boarding students at MAS DDI Pattojo; (2) describe the Arabic learning outcomes of non-boarding students; and (3) compare the learning outcomes of both groups. The research used a quantitative method with sociological and pedagogical approaches. The population consisted of 77 students from grades X and XI, with a saturated sampling technique involving 45 boarding students and 32 non-boarding students. Data were collected through observation, tests, and documentation, while data analysis applied descriptive and inferential statistical techniques. The findings show that both groups demonstrated relatively low performance in Arabic reading skills (mahārah qirā’ah). Boarding students achieved an average score of 30.89, while non-boarding students obtained an average score of 29.69. Furthermore, the Mann-Whitney U test revealed no significant difference between the two groups, as indicated by an Asymp. Sig. value of 0.615, which is greater than 0.05. These results indicate that the place of residence, whether boarding or non-boarding, is not a major factor influencing Arabic learning outcomes at MAS DDI Pattojo, suggesting that other educational or instructional factors may play a more significant role.

Students who are working on their undergraduate thesis often experience stress due to academic workload, pressure to graduate on time, and anxiety regarding their academic performance. Spirituality is considered one of the coping mechanisms that may help individuals achieve emotional calmness, life meaning, and self-acceptance, which potentially reduces stress. This study aims to determine the relationship between the level of spirituality and stress among students working on their thesis. This research used a quantitative method with a cross-sectional approach. A total of 134 students were selected using simple random sampling. The instruments used were the Daily Spiritual Experience Scale (DSES) to measure spirituality and the Perceived Stress Scale (PSS-10) to measure stress levels. Data analysis was performed using the Spearman Rank correlation test. The findings indicate a significant correlation between spirituality and stress levels with a p-value of 0,002. The Spearman correlation coefficient (r = -0,264) indicates a negative correlation, meaning that higher levels of spirituality are associated with lower stress levels among thesis-writing students. There is a significant negative relationship between spirituality and stress among students working on their undergraduate thesis. Increasing spirituality may serve as an effective coping strategy to reduce stress during the thesis completion process.

This study aims to analyze the effects of work motivation and career development on nurses’ performance through job satisfaction among nurses at Pertamina Balikpapan Hospital. Nurses’ performance is a key determinant of service quality and patient safety because nurses interact most intensively with patients and ensure continuity of nursing care. However, prior studies on the relationships among motivation, career development, job satisfaction, and performance have reported mixed findings. Therefore, further examination is needed by incorporating job satisfaction as a mediating variable to explain the mechanism of influence more comprehensively. This research employed an explanatory design with a quantitative approach. Primary data were collected using a Likert-scale questionnaire distributed to 165 permanent nurses selected through purposive sampling from a population of 292 nurses. Data were analyzed using variance-based SEM with SmartPLS 4, including outer model evaluation (convergent and discriminant validity) and construct reliability, as well as inner model assessment through the coefficient of determination, effect size, and hypothesis testing using bootstrapping. The results indicate that work motivation has a positive and significant effect on job satisfaction, and career development also has a positive and significant effect on job satisfaction. Job satisfaction has a positive and significant effect on nurses’ performance. In addition, work motivation and career development have positive and significant direct effects on nurses’ performance. Indirect effect testing confirms that job satisfaction mediates the relationship between work motivation and nurses’ performance and also mediates the relationship between career development and nurses’ performance. These findings emphasize that hospitals should strengthen strategies to enhance motivation and career development in a targeted manner while ensuring key sources of job satisfaction so that nurses’ performance improves sustainably.

This study aims to analyze the influence of HR Information Systems and Work Discipline on Employee Performance Through Job Satisfaction as an Intervening Variable at CV Multirejeki Selaras, Payakumbuh City. Data collection methods were through interviews and questionnaires. The population in this study was 40 employees. The data analysis method used was Structural Equation Modeling (SEM) using Partial Least Square (PLS). Based on the results of data analysis, it was found that HR Information Systems had a positive and significant effect on Job Satisfaction, Work Discipline had a positive and significant effect on Job Satisfaction, HR Information Systems had no and insignificant effect on Employee Performance, Work Discipline had no and insignificant effect on Employee Performance, Job Satisfaction had a positive and significant effect on Employee Performance, Job Satisfaction was able to mediate the effect of HR Information Systems on Employee Performance, Job Satisfaction was able to mediate the effect of Work Discipline on Employee Performance. The results of this study indicate that although the HR Information System and Work Discipline have a positive influence on Job Satisfaction, both do not have a direct influence on Employee Performance, but rather through the role of Job Satisfaction as a significant mediator.

Psychology personnel in primary healthcare centers (Puskesmas) play a strategic role in delivering mental health services at the primary level; however, they are frequently confronted with complex and multifaceted job demands. This study aims to examine the effects of workload and work stress on the job performance of psychology personnel in Puskesmas in Surabaya City. A quantitative approach with a correlational cross-sectional design was employed. The study population comprised all psychology personnel working in Puskesmas in Surabaya City, with total sampling applied, resulting in 63 respondents. Workload and work stress were measured using five-point Likert scales, while job performance was assessed based on monthly psychology service reports. Data were analyzed using multiple linear regression analysis. The results indicate that the majority of psychology personnel experienced high workload levels and relatively high work stress, whereas overall job performance was predominantly categorized as good. Regression analysis revealed that workload and work stress simultaneously had a significant effect on job performance, and partially both variables exerted a negative effect on performance. These findings suggest that although psychology personnel are generally able to maintain adequate performance, excessive workload and elevated work stress may potentially undermine performance in the long term if not properly managed. Therefore, this study highlights the importance of systematic workload management and work stress intervention strategies to sustain the quality of psychological services in primary healthcare settings.

This study aims to analyze the influence of port infrastructure, logistics connectivity, and fleet capacity on the performance of sea tolls in Indonesia. The approach used in this literature review study is descriptive qualitative. The data collection technique used is a literature study or review of relevant previous articles published between 2021 and 2026. The technique used in this literature review is comparative analysis. The data used in this descriptive qualitative approach came from previous studies relevant to this study and sourced from academic online media such as Thomson Reuters Journal, Springer, Taylor & Francis, Scopus Q2-Q4 Emerald, Elsevier, Sage, Web of Science, Sinta 2-5 Journal, DOAJ, EBSCO, Google Scholar, Copernicus, and digital reference books. The results of the study show that: 1) Port infrastructure affects sea toll performance; 2) Logistics connectivity affects sea toll performance; 3) Fleet capacity affects sea toll performance.

This research evaluates the effectiveness of human capital development policies in Indonesia within the education and health sectors during the periods of 2015–2019 and 2020–2024. The analysis focuses on strategic programs implemented by the Ministry of Education and Culture and the Ministry of Health by comparing planned targets with the realization of performance indicators as stated in the Strategic Plan (Renstra) documents. The study employs a qualitative evaluative approach supported by descriptive quantitative data derived from official planning and performance reports. The findings indicate that during the 2015–2019 period, programs emphasizing the expansion of basic education and health services were relatively effective in increasing participation rates and improving equitable access. In contrast, programs aimed at enhancing the quality of human resources, particularly teacher development and institutional capacity building, showed lower levels of effectiveness due to weak performance measurement systems and inconsistent data reporting. During the 2020–2024 period, the effectiveness of most education and health programs declined significantly as a result of external shocks caused by the COVID-19 pandemic. However, health programs with strong financial protection mechanisms, such as the National Health Insurance (JKN), demonstrated greater resilience compared to other programs. The study concludes that the effectiveness of human capital development policies is strongly influenced by the clarity of performance indicators, consistency in program implementation, institutional capacity, and the ability of policies to adapt to external disruptions.