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In addition to the key findings, the study also emphasizes the importance of fostering a deeper understanding of the role of audit committees within the broader context of financial governance. Despite the recognition of the audit committee’s importance in improving the quality of financial reporting, the findings indicate that there is a significant gap in the implementation of best practices across private commercial banks in Iraq. This gap is attributed to the lack of full compliance with regulatory requirements regarding the composition of audit committees, particularly in terms of ensuring independence and financial expertise. The study further reveals that while the audit committee's independence and expertise play a crucial role in enhancing the quality and relevance of financial information, many banks still struggle to implement effective oversight mechanisms. This situation is exacerbated by the complex regulatory environment in Iraq, where overlapping supervisory authorities and weak enforcement of governance mechanisms hinder the effectiveness of financial reporting processes. The lack of coordination between audit committees and internal audit units, as well as the limited ability to assess financial performance, further undermines the oversight function of audit committees. To address these challenges, the study suggests several recommendations, including enhancing the legal framework to enforce stricter compliance with the formation of qualified and independent audit committees. Additionally, increasing awareness and training among stakeholders about the importance of audit committees and their roles in ensuring transparent and reliable financial disclosures is crucial. Strengthening the oversight function and improving coordination between audit committees and internal audit units will also help in mitigating the existing weaknesses in the financial reporting process. These steps are essential for improving the reliability of financial information, thereby fostering investor confidence and contributing to the overall stability of the banking sector in Iraq.

This study is motivated by the importance of emotion regulation skills among university students who are in the transitional phase toward early adulthood, where academic, social, and personal pressures can affect psychological well-being. Spiritual intelligence is considered one of the factors that can support this ability. The purpose of this study is to determine the relationship between spiritual intelligence and emotion regulation among students of the Faculty of Science, Technology, and Health, Universitas Sahid Surakarta. This research employed a quantitative method with a correlational design. The sample consisted of 196 students selected through purposive sampling. The research instruments were a spiritual intelligence scale and an emotion regulation scale, both of which had been tested for validity and reliability. Data were analyzed using Pearson Product Moment correlation. The results showed a very strong and significant positive relationship between spiritual intelligence and emotion regulation (r = 0.883; p < 0.05). These findings indicate that the higher the students’ spiritual intelligence, the better their ability to recognize, evaluate, and manage emotions. The implications of this study emphasize the importance of developing spiritual intelligence in higher education settings as an effort to enhance students’ emotion regulation abilities.

Abstract. The advancement of broadcasting technology has driven the demand for reliable and efficient automation systems, particularly in managing the transition from broadcast content to advertisement segments. In this context, the present study proposes the application of the Single Tone Trigger (STT) method as an automatic triggering mechanism to systematically regulate content switching. This method utilizes a single-frequency audio signal embedded within the primary broadcast, which can be detected by the receiving system. The detection of this signal initiates an automatic content transition without requiring intervention from playout operators. A key advantage of this approach lies in its ease of integration with conventional broadcasting systems and its ability to reduce manual involvement that has traditionally been essential in broadcast content management. Through a series of tests, the system demonstrated high signal detection accuracy, low latency, and optimal operational reliability. These findings indicate that the Single Tone Trigger method can significantly enhance workflow efficiency within the broadcasting industry. Overall, this approach presents substantial potential for broad implementation as an automation solution that is not only stable and cost-effective, but also adaptive to the operational demands of modern broadcasting.   Keywords: Automatic Transition, Broadcast Automation, Single Tone Trigger (STT).

Environmental issues are complex and increasingly important. This is also true in the industrial sector, particularly in the culinary industry. Currently, public awareness of environmental issues is increasing, leading consumers to consider eco-friendly factors in their daily lives. The concept of eco-friendliness in the coffee shop industry has become an increasingly popular trend. Especially in the food and beverage (F&B) industry, which plays a significant role in waste production, particularly plastic and food waste. Therefore, the concept of eco-friendly practices has emerged in the F&B industry. This can take the form of using environmentally friendly food ingredients, eco-friendly packaging, and the café concept itself, which conveys an eco-friendly image that can increase consumer purchasing interest. This is implemented by Fore Cafe and Coffee Galaxy Bekasi. This study aims to investigate how the eco-friendly concept is implemented and its impact on consumer purchasing interest at Fore Cafe & Coffee Galaxy Bekasi. The study employs a quantitative approach with a sample and population of 99 consumers of Fore Cafe & Coffee Galaxy Bekasi, selected randomly. The analysis uses validity tests, reliability tests, normality tests, and T-statistical test. The results of the research and data processing using SPSS version 25 showed that the Eco-Friendly concept had an effect on increasing consumer interest in purchasing Fore Cafe & Coffee Galaxy Bekasi, and certainly had a positive effect on environmental conditions.

The rapid growth of e-commerce platforms has significantly transformed the way consumers share and access product feedback. One of the widely used platforms in Indonesia is Shopee, where customers actively provide reviews of various products, including local skincare brands such as Kahf facial wash. Customer reviews on e-commerce platforms contain valuable information that can be analyzed to understand consumer opinions and preferences. Sentiment analysis, as a branch of natural language processing, enables the classification of textual data into categories such as positive, negative, or neutral. This study aims to classify Shopee user sentiments regarding Kahf facial wash products by implementing the Multinomial Naïve Bayes algorithm, a well-known probabilistic classifier suitable for text categorization. The research methodology consisted of several preprocessing stages, including data cleansing, case folding, tokenizing, stopword removal, and stemming, to prepare raw review texts for further analysis. For feature representation, the Term Frequency–Inverse Document Frequency (TF-IDF) method was applied to capture the importance of words across documents. To evaluate the classification performance, K-Fold cross-validation was employed with K values of 4, 5, 6, and 10 to ensure model reliability and robustness. Considering the issue of imbalanced datasets in user-generated reviews, the Synthetic Minority Over-sampling Technique (SMOTE) was utilized to balance the distribution of sentiment classes. Based on the confusion matrix, the Multinomial Naïve Bayes algorithm demonstrated effective performance in classifying sentiments, achieving satisfactory levels of accuracy, precision, and recall across different folds. These results indicate that the algorithm is capable of handling sentiment analysis tasks for local product reviews effectively. The findings of this study are expected to provide meaningful insights for businesses in understanding consumer perceptions, thereby supporting decision-making processes in product development, marketing strategies, and customer engagement for local brands.

Preeclampsia is one of the most serious complications in pregnancy, characterized by hypertension and proteinuria, and it poses a significant risk of maternal and fetal morbidity and mortality if not detected and managed promptly. Early detection is crucial, yet clinical diagnosis often faces challenges due to the variability of symptoms and uncertainty in medical decision-making. To address this issue, this study aims to develop an expert system for diagnosing preeclampsia by employing the Dempster-Shafer method, which is known for its ability to handle uncertainty and incomplete information in complex domains such as healthcare. A case study was conducted at Bidadari General Hospital, where data on clinical symptoms and patient medical records were collected and analyzed. The development process of the expert system followed systematic stages, including knowledge acquisition from obstetrics specialists, designing the knowledge base, constructing inference rules, and integrating the Dempster-Shafer algorithm for decision support. The system was subsequently tested using real-case scenarios of pregnant women suspected of having preeclampsia. Evaluation results demonstrated that the system achieved an accuracy rate of 92% in differentiating between preeclampsia and eclampsia, based on belief and plausibility measures combined with symptom analysis. These findings indicate that the proposed system can effectively support medical personnel by providing diagnostic recommendations with a high degree of reliability. In addition, the system offers efficiency in the clinical workflow by minimizing diagnostic errors and reducing delays in treatment initiation. Therefore, this expert system has the potential to become a valuable clinical decision support tool for early detection, risk assessment, and management of preeclampsia. Future development may focus on expanding the knowledge base, integrating real-time patient monitoring data, and enhancing usability to ensure broader applicability in diverse healthcare settings.

The increasing number of mental health disorders in various countries has created an urgent need for innovation in the diagnosis and treatment process. This problem not only impacts individuals' quality of life but also creates a significant social and economic burden. One solution that is beginning to be widely researched is the use of artificial intelligence (AI) in the field of mental health. This research used a literature review of various previous studies discussing the role, application, and impact of AI. The results of the review indicate that AI technology, particularly in the form of digital applications such as chatbots, has great potential to support the recovery process for patients with mental disorders. AI-based chatbots can provide responsive, two-way interactions, so users feel heard and receive initial emotional support. One technical approach used is Natural Language Processing (NLP), which enables the system to understand natural human language. Simultaneously, Long Short-Term Memory (LSTM) algorithms are used to analyze language patterns and detect symptoms of depression more accurately. Various studies have reported that the application of NLP and LSTM can improve the reliability of diagnoses and provide responses tailored to user needs. Furthermore, AI can provide personalized recommendations, tailor interventions to the user's condition, and monitor mental health developments in real time. This has the potential to assist mental health practitioners in making faster and more informed decisions. However, the adoption of AI among practitioners remains relatively low. Influencing factors include limited technological understanding, limited infrastructure, and debates over ethical aspects and data privacy. Therefore, while AI has significant potential to improve the quality of mental health services, regulations, ethical guidelines, and synergy between technology and healthcare professionals are needed to ensure safe and effective implementation.

Asynchronous motors, commonly known as induction motors, are widely utilized due to their robustness, reliability, and efficiency in both industrial and household applications. These motors typically operate by converting electrical energy into mechanical energy through the interaction between a rotating magnetic field and the rotor. Under normal operating conditions, the rotor speed is always slightly less than the speed of the magnetic field, which is known as "slip." However, when the slip becomes negative, meaning that the rotor speed exceeds the speed of the rotating magnetic field, the motor begins to function as a generator. This condition occurs when the motor is driven above its synchronous speed by an external mechanical force, causing the rotor to generate electrical power. Using an asynchronous motor as a generator offers several notable advantages. One of the key benefits is its ability to produce a pure sine wave voltage, which is crucial for various applications that require stable and high-quality electrical power. Since these motors do not use brushes, they are free from the problems associated with brush wear and maintenance. Moreover, they do not generate radio frequency interference (RFI), making them suitable for environments sensitive to electromagnetic disturbances. The use of an asynchronous motor as a generator also provides the ability to function as a rotary phase converter. This is especially beneficial in applications where three-phase power is unavailable, but the load requires it. To facilitate this process, a capacitive voltage is required to induce excitation in the rotor. The capacitive current is supplied by an additional capacitor, which is installed in parallel with the motor output. This capacitor helps maintain the necessary phase shift and enables the motor to generate the required three-phase power.

This analysis aims to evaluate the influence of Islamic Work Ethic and Task Load Level on Employee Productivity and Job Satisfaction at Kendal Islamic Hospital. Islamic Work Ethic in this study is measured through five main dimensions, namely siddiq (integrity), istiqamah (steadfastness), fathanah (intellectual intelligence), amanah (reliability), and tabligh (communication capacity). Meanwhile, Task Load Level is understood as work pressure reflected by three main indicators, namely physical fatigue, emotional fatigue, and psychological fatigue. This study uses a quantitative approach with an explanatory research design to test the causal relationship between variables. Primary data were collected through the distribution of structured questionnaires to hospital employees using probability sampling techniques, so that respondent representation is more assured. Data analysis was carried out using multiple linear regression through SPSS software, to determine the level of direct and indirect influence between variables. The results of the study indicate that Islamic Work Ethic has a positive and significant influence on Employee Job Satisfaction and Productivity, indicating that the application of Islamic values in work ethic can encourage motivation, loyalty, and performance. Conversely, the Level of Task Load has a significant negative effect on Job Satisfaction, indicating that excessive workload can reduce satisfaction, although it is not proven to have a significant impact on Employee Productivity. Furthermore, Job Satisfaction is proven to have a positive and significant influence on Employee Productivity, so it can play a role as an important mediating variable in the relationship between work ethic and performance. This study provides a theoretical contribution to the development of human resource management concepts based on Islamic values, while also offering practical recommendations for hospital managers to strengthen Islamic work ethic and manage workload proportionally to improve employee welfare and performance.  

This study aims to analyze the influence of content marketing and live streaming on purchasing decisions for fashion products among Generation Z users of the TikTok platform. In the era of digitalization and social media dominance, TikTok has emerged as one of the most influential platforms shaping consumer behavior, particularly for the younger generation. The research adopts an associative quantitative approach using a questionnaire survey distributed to 102 respondents who actively use TikTok for fashion-related content. The collected data were analyzed through Structural Equation Modeling–Partial Least Squares (SEM-PLS) using SmartPLS 4 to test the hypothesized relationships between variables. The results indicate that both content marketing and live streaming significantly and positively affect purchasing decisions. The path coefficients of 0.361 for content marketing and 0.521 for live streaming demonstrate their substantial contribution. Furthermore, the research model yields an R-squared value of 0.640, suggesting that these two independent variables collectively explain 64% of the variance in purchasing decisions among Generation Z. In addition, the validity and reliability tests confirm that all constructs fulfill the eligibility criteria, reinforcing the robustness of the measurement model. These findings emphasize that content-based marketing strategies, when designed to be engaging, interactive, and visually appealing, are highly effective in fostering consumer interest and driving purchase intention. Live streaming, in particular, serves as a powerful marketing tool by offering real-time interaction, product demonstration, and a sense of authenticity that resonates strongly with Generation Z’s consumption patterns. The implications of this research highlight the strategic importance for fashion brands to optimize their digital marketing practices by integrating creative content marketing and live streaming features on TikTok.

This study aims to examine the influence of motivation, work enthusiasm, and work discipline on the performance of employees at PT. Pos Indonesia (Persero), Kediri Branch Office. A quantitative research approach was employed with a total population of 64 respondents. The sampling technique applied was saturated sampling, resulting in all 64 members of the population being used as the research sample. Data analysis was conducted using SPSS 25.0. The research process included validity and reliability assessments, classical assumption evaluations, multiple linear regression analysis, partial testing (t-test), simultaneous testing (F-test), and calculation of the coefficient of determination (R²). The results reveal that, individually, motivation, work enthusiasm, and work discipline each have a significant impact on employee performance. Moreover, when considered together, these three factors also exert a significant influence on employee performance.

This study aims to investigate the extent to which communication and occupational health and safety (OHS) influence employee performance at PT Sinergi Aitikom, South Jakarta, both partially and simultaneously. The research problem is based on the importance of effective communication and the implementation of OHS in creating a safe, productive work environment, and supporting the achievement of optimal performance. The research approach uses a quantitative method with an associative design, which allows for analysis of relationships between variables. The independent variables include communication (X1) and occupational health and safety (OHS) (X2), while the dependent variable is employee performance (Y). The study population is all 81 employees of PT Sinergi Aitikom, and because the number is relatively small, a saturated sampling technique is used so that the entire population becomes the research sample. Data analysis was conducted through validity and reliability tests, classical assumption tests, regression analysis, correlation coefficients, coefficients of determination (R²), and hypothesis testing using t-tests and F-tests. The results showed that the OHS variable significantly influences employee performance, as indicated by a calculated t-value of 10.698, which is greater than the t-table (1.990), with a significance value of 0.000 (<0.05). Furthermore, the F-test results reinforced this finding, with a calculated F-value of 304.857, which is greater than the F-table (3.11), and a significance value of 0.000 (<0.05). This proves that communication and OHS simultaneously have a strong influence on employee performance. The coefficient of determination (R²) of 0.887 indicates that 88.7% of the variation in employee performance can be explained by communication and OHS, while the remaining 11.3% is influenced by other factors outside this study. Thus, effective communication and sound OHS implementation have proven to be key factors in improving employee performance in the company.

This study aims to determine the effect of group guidance services with role-playing techniques on the interpersonal communication skills of seventh-grade students at MTs Nurus Salam Deli Tua. Interpersonal communication skills are crucial for adolescents to interact effectively with their social environment. This study employs a quantitative approach with a quasi-experimental method in the form of a one-group pretest-posttest design. The population of this study consisted of 65 students, with a sample of 10 students selected purposively based on the results of initial observations. The instrument used was an interpersonal communication questionnaire that had been tested for validity and reliability. Data analysis was performed using a t-test. The results showed a significance value of 0.000 < 0.05, indicating a significant effect of group guidance services with role-playing techniques on students' interpersonal communication skills.

This study aims to analyze the influence of hard skills and soft skills on job readiness through self-efficacy as a mediating variable in students at the Faculty of Economics and Business, Yogyakarta State University. The background of the study is rooted in the increasing demands of the job market, which emphasize not only technical competence but also interpersonal skills and individual confidence in their own capabilities. As the world of work becomes increasingly competitive, the ability to balance technical skills with psychological readiness becomes a crucial factor. This study employed a quantitative approach with descriptive analysis and path analysis. A total of 229 respondents were selected using a two-stage random sampling method to ensure adequate representation. The data were analyzed using SmartPLS to test the validity, reliability, and fit of the structural model. The results revealed that hard skills had a significant but negative effect on job readiness, while soft skills showed a positive but statistically insignificant effect. Both hard and soft skills were shown to have a positive and significant effect on self-efficacy, with self-efficacy having a significant effect on job readiness. Further findings indicate that self-efficacy mediates the relationship between hard skills and job readiness, but not the relationship between soft skills and job readiness. Overall, this research emphasizes the importance of integrating hard skills, soft skills, and self-efficacy in building student job readiness. The implication is that universities need to design curricula and student development programs that not only strengthen technical competencies but also foster interpersonal skills and self-confidence so that graduates can compete in a dynamic job market.

This study explores the influence of digital marketing, service quality, and product innovation on customer satisfaction among Skintific skincare consumers on TikTok Shop. Employing a quantitative, explanatory research design, the study used purposive sampling to collect 200 valid responses from consumers who had purchased Skintific products via TikTok Shop. Data were collected through an online questionnaire and analyzed using multiple linear regression with SPSS, preceded by validity, reliability, and classical assumption tests. The results revealed that product innovation had the most significant impact on customer satisfaction (β = 0.589, p < 0.001), followed by service quality (β = 0.343, p < 0.001). However, digital marketing did not have a significant direct effect on customer satisfaction (β = 0.019, p = 0.746). The model explained 86.9% of the variance in customer satisfaction (R² = 0.869), indicating strong combined effects from the three factors. These findings suggest that post-purchase factors, particularly product innovation and service quality, are more decisive in influencing customer satisfaction than promotional efforts alone. Managerial implications highlight the importance of continuous product development, enhancing service responsiveness and reliability, and integrating digital marketing with value delivery to optimize customer satisfaction. The study contributes to social commerce literature by clarifying the distinct roles of marketing, service quality, and innovation in the context of TikTok Shop, providing both theoretical insights and practical guidance for brand strategy in social commerce platforms. This research adds to the understanding of how businesses can strategically leverage product innovation and service excellence to enhance consumer satisfaction and foster long-term customer loyalty in the competitive social commerce landscape.

The effectiveness of reporting within the reporting information system at Community Health Centers (Puskesmas) is crucial for supporting data‑driven decision‑making, health‑program planning, and performance monitoring. Accurate and timely reporting enables healthcare administrators to analyze trends, allocate resources efficiently, and improve patient outcomes through evidence‑based interventions. This article analyzes the factors influencing reporting effectiveness at Puskesmas in Serang Regency, including technological, human‑resource, and organizational factors. The study employs a literature‑review and case‑analysis approach, highlighting challenges and offering recommendations to improve reporting effectiveness. The results indicate that limitations in infrastructure, staff competency, digital literacy, as well as management support and policy, are key factors that must be addressed to optimize the reporting system in Serang Regency’s Puskesmas. Technological barriers—such as inadequate hardware, software, and internet connectivity—often hinder the seamless collection and transmission of health data. Human‑resource challenges, including insufficient training and low digital literacy among staff, can lead to data‑entry errors and delays. Organizational factors—such as clear policies, standard operating procedures, and a supportive management culture—are also essential for sustaining high‑quality reporting practices. Furthermore, the integration of health informatics and continuous quality‑improvement initiatives can enhance the reliability and usability of reported data, ultimately supporting better health outcomes at the community level. The study concludes that a holistic approach—encompassing technological upgrades, ongoing staff development, and strong organizational leadership—is necessary to ensure the effectiveness and sustainability of reporting systems in primary‑healthcare settings.

This study aims to predict the potential bankruptcy of PT Argo Pantes Tbk for the period 2014–2024 using the Zmijewski X-Score model. The research adopts a quantitative method based on secondary data obtained from the company’s published annual financial statements. The Zmijewski model was selected because of its effectiveness in assessing companies with unstable financial conditions and its ability to provide a more accurate reflection of financial distress compared to other models. The analysis process involved calculating the X-Score for each year within the observation period and interpreting the results according to the criteria of the model. The findings indicate that for the entire study period, the calculated X value was consistently greater than or equal to zero. This outcome signifies that the company is in a condition classified as potentially bankrupt. Furthermore, the model demonstrated 100% accuracy in describing the company’s actual financial situation, since PT Argo Pantes Tbk consistently recorded net losses throughout the period of analysis. These losses were not incidental but reflected a long-term pattern of weak financial performance, limited profitability, and declining competitiveness in the textile industry. The results highlight that PT Argo Pantes Tbk has been operating under severe financial distress for a prolonged period, with no indication of recovery during the years observed. The persistent losses and negative financial indicators reinforce the conclusion that the company is in an unhealthy condition. The study confirms the applicability and reliability of the Zmijewski X-Score as a bankruptcy prediction tool in the Indonesian context, particularly for firms experiencing prolonged instability. Overall, the study provides valuable insights into financial distress analysis and underscores the importance of early bankruptcy prediction models in supporting stakeholders, investors, and regulators in making informed decisions.

Government websites must meet high quality standards to ensure optimal functionality, reliability, and security for users. This study aims to test the quality of the Rimba Sekampung Village website based on ISO 29119:2022 standards. Testing is carried out using a variety of methods, including functional, non-functional, usability, and compatibility testing. The data was collected through a series of trials using tools such as Selenium IDE and Apache JMeter. The test results show that this website has a functional test success rate of 97% and an overall feasibility rate of 88.30%. Although most of the features have been tested well, there are some aspects that still need improvement, such as the scope of testing against the needs or features that only reach 56%. This study emphasizes the importance of standard-based testing in improving the quality of website-based digital services at the consumer sector level.

This study aims to analyze the effect of training and human resource development on employee performance at the Social Service Office of Bima City. The research was motivated by the low level of employee productivity, limited budget allocation for development programs, and the tendency of some employees to delay task completion. The study employs a quantitative approach with an associative method. The population consists of 59 employees, with a sample of 35 civil servants selected through purposive sampling. Data were collected using questionnaires, observation, interviews, and documentation. The analysis techniques include validity and reliability tests, classical assumption tests, multiple linear regression, t-test, and F-test. The findings show that both training and human resource development have a significant and positive impact on employee performance. Training improves employee skills, while development efforts enhance competencies to meet organizational demands. The study suggests that structured training and development programs should be optimized to improve public service performance.

This study aims to analyze the influence of Personal Branding, Perceived Value, and Product Quality on consumer purchasing decisions for Carolline Crafty Crochet home industry knitting craft products. The background of this study is based on the increasing competition in the handicraft business, so that business owners are required to be able to build a strong personal image, provide perceived value to consumers, and maintain product quality to increase purchasing attractiveness. The data source used is primary data obtained through distributing questionnaires to respondents. The population of this study were consumers who had purchased Carolline Crafty Crochet products both offline and online. The sampling technique used a nonprobability sampling method with a purposive sampling approach. The calculation of the number of samples used the Lemeshow formula and obtained 96 respondents who met the research criteria. Data analysis was carried out with the help of SPSS version 27 software through validity tests, reliability tests, classical assumption tests, multiple linear regression analysis, and partial and simultaneous hypothesis testing. The results showed that the variables Personal Branding, Perceived Value, and Product Quality had a positive and significant effect on consumer purchasing decisions. This indicates that the stronger the business owner's personal branding, the higher the perceived value felt by consumers, and the better the quality of the products offered, the greater the likelihood of consumers making purchasing decisions. These findings provide practical implications for small and medium enterprises (SMEs), particularly in the handicraft industry, that marketing strategies based on personal branding, increasing perceived value, and controlling product quality need to be optimized to increase consumer loyalty and purchasing interest. Thus, this study emphasizes the importance of integrating aspects of personal branding, perceived value, and product quality in shaping purchasing decisions, which can serve as a reference for developing sustainable business strategies in today's competitive era.