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The purpose of this study was to determine the effect of the Think Talk Write Cooperative Type model on the motivation to learn Christian Religious Education and Character Education of Class VIII Students of SMP Negeri 2 Siborongborong in the 2024/2025 Academic Year. The method used in this study is a quantitative research method. The population is all Christian students of class VIII of SMP Negeri 2 Siborongborong in the 2024/2025 Academic Year totaling 222 people and a sample of 55 people was determined, namely 25% of the population using random sampling techniques. Data were collected with a positive questionnaire of 40 items, namely 25 items for variable X and 15 items for variable Y. The results of the data analysis showed that there was an influence of the Cooperative Think Talk Write Type model on the motivation to learn Christian Religious Education and Character Education of Class VIII Students of SMP Negeri 2 Siborongborong in the 2024/2025 Academic Year as evidenced by the following data analysis: 1) Analysis requirements test: a) positive relationship test obtained rxy value = 0.584> rtable ( = 0.05, n = 55) = 0.226. b) Significant relationship test obtained tcount = 5.232> ttable ( = 0.05, dk = n-2 = 53) = 2,000. 2) Influence test: a) Regression equation test, obtained regression equation . b) Regression determination coefficient test (r2) = 34.1%. 3) Hypothesis testing using the F test obtained Fcount > Ftable = ( = 0.05, df numerator k = 25, df denominator = n-2 = 55-2 = 53) which is 27.26 > 1.39. Thus Ha is accepted and H0 is rejected.

This study aims to analyze the effect of the level of implementation of accrual-based International Public Sector Accounting Standards (IPSAS) on the fiscal transparency of the central government. In addition, this study also examines the differences in the level of IPSAS implementation among OECD, non-OECD, and BRICS countries. The study sample consisted of 20 countries selected through a purposive sampling technique based on three main criteria: (1) the central government has used accrual-based financial reports, either partially or fully; (2) the country has implemented IPSAS for more than five years; and (3) the country is listed in the Open Budget Survey. This study uses panel data covering the years 2015, 2017, 2019, 2021, and 2023. The independent variable in this study is the level of implementation of accrual-based IPSAS as measured by three main indicators: commitment to accruals, accrual reporting, and accrual policies. Meanwhile, the dependent variable, fiscal transparency, is measured using the Open Budget Index score, which reflects the level of openness of the central government budget to the public. The analysis was conducted using panel data regression with a random effects model approach. The results show that the level of accrual-based IPSAS implementation has a positive effect on fiscal transparency, but this effect is not statistically significant. However, there are significant differences in the level of IPSAS implementation among OECD, non-OECD, and BRICS countries. This finding indicates that IPSAS implementation in various countries is influenced by different institutional factors and fiscal capacities, thus requiring strong institutional support to promote more effective fiscal openness.

This study presents a machine learning approach for predicting the dimensions of microstrip antenna slots based on antenna performance parameters such as frequency, gain, directivity, return loss (S11), radiation efficiency, and VSWR. A two-phase methodology was employed. In the first phase, ten regression algorithms were evaluated, and Random Forest was identified as the most effective model based on Mean Absolute Error (MAE) and R-squared (R²) scores. In the second phase, hyperparameter tuning was conducted using Grid Search to further improve the model’s performance. The optimized Random Forest model demonstrated consistent improvements in predictive accuracy, with R² values increasing across all output variables. These results indicate that the combination of regression-based modeling and systematic hyperparameter tuning is effective for capturing complex relationships in antenna design tasks. The proposed approach offers a promising data-driven alternative for geometric prediction in microstrip antenna development, particularly when analytical models are insufficient.

The study presents a comprehensive framework for optimizing customer retention budget by integrating clustering, classification, and mathematical optimization techniques. The study begins with the IBM Telco dataset, which is prepared through data cleansing, encoding, and scaling.  In the preliminary phase, customer segmentation is performed using K-Means clustering, with k = 3 and k = 4 identified as optimal based on the elbow method and Silhouette score. The configurations produced three (Premium, Standard, Low) and four (Premium, Standard Plus, Standard, Low) customer segments based on purchase preferences, which served as input features for churn prediction. In the second phase, the dataset was divided into training and test sets in an 80:20 ratio, followed by data balancing using the Synthetic Minority Over-sampling Technique (SMOTE) and Edited Nearest Neighbors (ENN). Multiple classification algorithms were evaluated, including Naive Bayes (NB), Random Forest (RF), Categorical Boosting (CatBoost), Light Gradient Boosting Machine (LightGBM), Extreme Gradient Boosting (XGBoost), Gradient Boosting (GB), Support Vector Machine (SVM), Logistic Regression (LR), K-Nearest Neighbors (KNN), and Multi-Layer Perceptron (MLP) using F1-score as the performance metric. CatBoost and LightGBM, with k values of 3 and 4, respectively, were the highest-performing classification models, with only minimal differences in performance.    Ultimately, customer segmentation established customer prioritization, whereas churn prediction assessed customer churn likelihood. Four distinct configurations were assessed utilizing mixed-integer linear programming (MILP) to optimise retention budget allocation within uniform budget constraints, discount amounts, and churn thresholds. In both the k=3 and k=4 scenarios, CatBoost surpassed LightGBM, with CatBoost at K=3 effectively discounting 66% of at-risk consumers across all three segments, hence improving the intervention's efficacy and budget allocation, making it the ideal choice for maximizing customer retention. The results demonstrate the importance of segmentation in enhancing retention budgeting and budget optimization, particularly concerning parameter sensitivity.

The problem in the research is that the work given exceeds the provisions of written regulations, company leaders do not pay enough attention to their employees or do not provide enough motivation to their employees, performance fluctuates from year to year because employees are less careful in their work. The aim of this research is to determine the workload and motivation of employee performance at PT. Mandiri Abadi Permai. The type of this research is quantitative. The population in this research is employees of PT. Mandiri Abadi Permai, totaling 140 respondents. Determining the number of samples using the Slovin formula was 58 respondents, while the sampling technique was carried out randomly. The data sources in this research are primary and secondary data. Then the data collection methods in this research are observation, interviews, questionnaires and documentation. Meanwhile, the data analysis technique used is multiple linear regression analysis. Multiple linear regression test results Y=8.137+0.5221+0.532X2+e. The results of the test (t) or partial test show that workload has a positive and significant effect on employee performance which can be seen from tcount 6.477>ttable 2.004 and the Motivation variable has a positive and significant effect on employee performance where it can be seen tcount 11.166>ttable value 2.004. Then simultaneously (F test), the F value is 83.947> F table 3.16. So that workload and motivation have a positive and significant effect on employee performance at PT. Mandiri Abadi Permai. The results of the coefficient of determination for the Adjusted R square value are 0.744 (74.4%). So it can be said that 74.4% of the variation in the independent variables in workload and motivation contributes to employee performance variables at PT. Madiri Abadi Permai, while the remaining 25.6% is influenced by other variables outside the model.

The food and beverage subsector of the manufacturing industry, despite experiencing positive growth, still faces challenges in maintaining financial performance stability, such as high operational costs, suboptimal capital structure, and efficiency differences across company scales. This study aims to examine the effect of operational efficiency, leverage, and firm size on financial performance, both partially and simultaneously, in food and beverage manufacturing companies listed on the Indonesia Stock Exchange (IDX) for the 2022–2024 period. The sample consists of 16 companies selected using purposive sampling, with a total of 48 observations. This research applies a quantitative approach using panel data regression analysis and hypothesis testing through partial (t-test) and simultaneous (F-test) methods with STATA version 14. The best model used is the Random Effect Model (REM), selected through Chow, Hausman, and Lagrange Multiplier tests. The findings indicate that leverage has a significant negative effect on financial performance when tested partially, while operational efficiency and firm size do not have a significant partial effect. However, when tested simultaneously, operational efficiency, leverage, and firm size significantly influence the financial performance of food and beverage manufacturing companies listed on the IDX.  

One of the key factors in a company’s success is its human resources, particularly employees who are committed to fulfilling their responsibilities within the organization. This study aims to analyze the mediating role of job satisfaction in the effect of perceived organizational support on the organizational commitment of employees at The Trans Resort Bali. The study involved a sample of 59 employees. The sampling method used was proportional stratified random sampling. Data were collected through the distribution of questionnaires. The analysis technique employed in this study was Structural Equation Modeling (SEM) using the Partial Least Squares (PLS) approach. The results indicate that perceived organizational support has a positive and significant effect on organizational commitment. Perceived organizational support also has a positive and significant effect on job satisfaction. Furthermore, job satisfaction positively and significantly affects organizational commitment. Job satisfaction is proven to positively mediate the effect of perceived organizational support on organizational commitment.

The research aimed to analyze the relationship between the financial literacy of financial report users and the required level of disclosure, and to propose an intelligent mechanism based on artificial intelligence techniques to customize report content. The research variables were identified as: financial literacy (high, medium, low) and disclosure level (basic, medium, advanced), with a study of the effects of age and educational level. The research adopted a mixed methodology (descriptive and analytical) using machine learning models (Random Forest) and analysis of a questionnaire consisting of 15 questions. The research sample included 150 participants from Baghdad Bank and Asia Islamic Bank of Iraq, with 155 questionnaires distributed (electronically and on paper), excluding 5 incomplete questionnaires. The results showed a strong positive correlation between financial literacy and the level of disclosure, where 75% of those with high financial literacy preferred advanced reports. The artificial intelligence model also recorded an accuracy of 82% in predicting the optimal level of disclosure. The research recommended adopting intelligent customizable financial reports through artificial intelligence and enhancing users' financial literacy to improve decision quality.

This study is motivated by the crucial role of government spending and domestic investment (PMDN) in driving economic growth, particularly in Bali Province, which is heavily reliant on the tourism sector and vulnerable to external shocks such as the COVID-19 pandemic. The objective of this research is to analyze the influence of government expenditure in the general services and infrastructure sectors, as well as domestic investment, on Bali’s economic growth during the 2014–2023 period, both simultaneously and partially. This study employs panel data combining cross-sectional and time-series data from 9 regencies/cities in Bali Province over a 10-year period (2014–2023), using a Random Effect Model (REM) approach after conducting the Chow test, Hausman test, and Lagrange Multiplier test. The results show that, simultaneously, all independent variables significantly influence economic growth. Partially, government spending in general services, infrastructure, health, and education sectors has a positive and significant effect. Meanwhile, expenditure in economic services, domestic investment (PMDN), and the COVID-19 variable have a positive but statistically insignificant effect on economic growth in Bali Province. It is recommended that local governments improve the effectiveness of economic sector spending, promote equitable distribution of domestic investment, and accelerate economic diversification to reduce dependency on tourism and strengthen regional economic resilience.

Nephrolithiasis, commonly known as kidney stone disease, can be experimentally induced in animal models using ethylene glycol (EG) in combination with ammonium chloride, which closely mimics calcium oxalate stone formation in humans. This condition is associated with significant renal tissue injury, including glomerular atrophy, tubular necrosis, and hyaline droplet accumulation, ultimately impairing kidney function. The present study aimed to investigate the histopathological changes in the kidneys of EG-induced rats and evaluate the nephroprotective potential of combined avocado (Persea americana) and gooseberry (Physalis angulata) leaf extracts. A total of 30 male Sprague Dawley rats were randomly divided into five groups: a standard control (no induction), a negative control (EG-induced without treatment), a positive control (EG-induced and treated with a commercial nephroprotective agent), and two treatment groups receiving the combined extracts at different doses. Nephrolithiasis induction was performed over 28 days, followed by oral administration of the respective treatments. At the end of the experiment, kidney tissues were collected and processed for histological examination using hematoxylin-eosin staining to assess the extent of tissue damage. The negative control group exhibited the most severe histopathological alterations, with hyaline droplet formation reaching 15.0 ± 5.25%. In contrast, extract-treated groups demonstrated a marked reduction in tissue damage, with the most significant improvement observed in the group receiving 300 mg/kg avocado extract and 100 mg/kg gooseberry extract, which recorded hyaline droplet formation of only 5.27 ± 2.74%, a result comparable to that of the standard control group. These findings suggest that the combination of P. americana and P. angulata leaf extracts confers protective effects against EG-induced renal injury. Therefore, this herbal combination may represent a promising natural nephroprotective agent that warrants further investigation in preclinical and clinical settings.

This study aims to analyze how financial literacy and the frequency of use of financial technology (fintech) services affect the financial management patterns of students in the Economics Education Study Program at Universitas PGRI Wiranegara. The digitalization era has changed the way students manage their finances, which now combine traditional financial understanding with the implementation of digital technology innovations. This research uses a quantitative method with an explanatory approach, involving respondents selected through random stratification to ensure balanced representation. Data collection uses a Likert scale questionnaire instrument, while data analysis applies a multiple linear regression model. Empirical results prove that financial literacy and fintech utilization both have a significant and positive impact on students' financial management patterns. Together, these two factors can explain most of the variation in respondents' financial behavior. These findings emphasize the importance of integrating fundamental financial knowledge with the ability to adapt to digital technology as a foundation for forming effective financial management competencies in the modern era. In terms of implementation, the results of this study suggest strengthening the economics education curriculum that includes learning digital financial literacy and the use of fintech services that are wise and ethical.

Preeclampsia is a leading cause of maternal morbidity and mortality globally, including in Indonesia. It is characterized by hypertension and proteinuria, which appear after 20 weeks of pregnancy. The pathophysiology of preeclampsia is closely linked to oxidative stress, which is caused by abnormal placentation. One promising alternative treatment for managing preeclampsia is the use of natural ingredients with antioxidant properties, such as mulberry leaves (Morus alba). These leaves contain flavonoids, such as rutin and quercetin, which are known to have antioxidant effects. This study aims to examine the effects of mulberry leaf extract on blood pressure and proteinuria levels in male Wistar rats, using a preeclampsia model. The study employed a true experimental post-test only control group design. A total of 25 pregnant rats were randomly divided into five groups: a negative control group, a positive control group (which was induced with suramin to model preeclampsia), and three treatment groups receiving mulberry leaf extract at doses of 12.5, 25, and 50 mg/kgBW. Blood pressure and proteinuria levels were measured before and after 6 days of treatment. The results indicated that mulberry leaf extract significantly reduced both systolic and diastolic blood pressure and markedly lowered proteinuria levels. A significant relationship was observed between blood pressure and proteinuria (r = 0.528; p = 0.008), suggesting that the reduction in blood pressure was associated with a decrease in proteinuria. These findings suggest that mulberry leaf extract may be a promising natural complementary therapy for alleviating symptoms of preeclampsia, offering an alternative treatment approach to help manage this serious pregnancy complication. Further studies are needed to explore its potential in clinical applications.

Preeclampsia is a leading cause of maternal morbidity and mortality globally, including in Indonesia. It is characterized by hypertension and proteinuria, which appear after 20 weeks of pregnancy. The pathophysiology of preeclampsia is closely linked to oxidative stress, which is caused by abnormal placentation. One promising alternative treatment for managing preeclampsia is the use of natural ingredients with antioxidant properties, such as mulberry leaves (Morus alba). These leaves contain flavonoids, such as rutin and quercetin, which are known to have antioxidant effects. This study aims to examine the effects of mulberry leaf extract on blood pressure and proteinuria levels in male Wistar rats, using a preeclampsia model. The study employed a true experimental post-test only control group design. A total of 25 pregnant rats were randomly divided into five groups: a negative control group, a positive control group (which was induced with suramin to model preeclampsia), and three treatment groups receiving mulberry leaf extract at doses of 12.5, 25, and 50 mg/kgBW. Blood pressure and proteinuria levels were measured before and after 6 days of treatment. The results indicated that mulberry leaf extract significantly reduced both systolic and diastolic blood pressure and markedly lowered proteinuria levels. A significant relationship was observed between blood pressure and proteinuria (r = 0.528; p = 0.008), suggesting that the reduction in blood pressure was associated with a decrease in proteinuria. These findings suggest that mulberry leaf extract may be a promising natural complementary therapy for alleviating symptoms of preeclampsia, offering an alternative treatment approach to help manage this serious pregnancy complication. Further studies are needed to explore its potential in clinical applications.

This study aims to analyze the effect of capital structure, firm growth, audit quality, and foreign ownership on firm value, proxied by Price to Book Value (PBV), in consumer cyclical sector companies listed on the Indonesia Stock Exchange during 2018–2022. The analytical method used is panel data regression with the Random Effect Model (REM) approach. The results show that capital structure has a positive and significant effect on firm value. Conversely, firm growth, audit quality, and foreign ownership do not significantly affect firm value. These findings support signaling theory, which suggests that the use of debt within a reasonable threshold can boost investor confidence and enhance firm value. Therefore, it is recommended that corporate management focus on optimizing capital structure rather than relying solely on firm growth or external factors such as audit quality or foreign investors to improve firm value.

This study aims to examine the effect of the Problem Based Learning (PBL) model in Physical Education learning for volleyball at SMK Candra Naya Jakarta. The research method used was an experiment with a One Group Pretest-Posttest design. The sample consisted of 39 eleventh-grade students selected using Cluster Random Sampling technique. The research instrument was a test of overhead and underhand passing skills in volleyball. The results showed that the average pretest score of 14.05 increased to 17.77 in the posttest, with hypothesis testing (Paired Samples Test) yielding tcount > ttable (9.833) and a significance of 0.000 (p < 0.05). This proves that the PBL model significantly improves students' volleyball passing skills. Additionally, PBL encourages active participation, teamwork, and critical thinking skills. Therefore, the PBL model can be an innovative alternative in Physical Education learning, particularly for volleyball.

This research aims to examine how the predicted years in school and the unemployment rate influence labor force participation (TPAK) in Aceh Province. Across several cities and communities in Aceh, it employs secondary panel data from the Central Bureau of Statistics (BPS).  Panel regression analysis is done using the Random Effect Model (REM) approach in this study. The results show that TPAK is negatively and substantially affected by the unemployment rate, while the projected years of schooling have no significant statistical impact. TPAK changes are generally only marginally affected by either of these causes. The coefficient of determination reveals that the model explains only 8. 3% of the TPAK swings. Although education and unemployment are components of labor market behavior, other, more important variables are more crucial in influencing labor force participation in Aceh, as these results suggest.

This study aims to analyze the influence of economic growth and education quality on labor absorption in 27 regencies/cities of West Java Province during the 2020–2024 period using the Random Effect Model (REM) method. The estimation results show that economic growth has a positive and significant effect on labor absorption, with a coefficient of 0.322424 and a p-value of 0.0002. This indicates that regional economic growth contributes to increasing employment opportunities. On the other hand, the quality of education, measured by the average years of schooling, has a negative and insignificant effect on labor absorption, with a coefficient of -0.706782 and a p-value of 0.0755. These findings suggest that improvements in formal education do not automatically lead to increased labor absorption, likely due to a mismatch between graduate qualifications and labor market needs. The Adjusted R-squared value of 0.091650 indicates that the model explains only about 9.16% of the variation in labor absorption, with the remaining variation influenced by other unobserved factors. Therefore, strategic policies are needed, such as the development of labor-intensive sectors and the improvement of vocational education quality and relevance, to optimally enhance labor absorption in West Java.

This study aims to analyze the influence of discipline in congregational prayer and understanding of religious sermons (kultum) on the spiritual intelligence of 8th-grade students at SMPN 1 Jetis. Spiritual intelligence is important in shaping students' character and morals. However, several issues were identified, such as tardiness in congregational prayers, preference for sitting in the back rows, and lack of understanding of the messages conveyed in the sermons. This research employed a quantitative correlational non-experimental method with simple random sampling. Data collection was conducted through questionnaires and documentation.The results of the study show that: (1) Discipline in congregational prayer has a significant effect on spiritual intelligence, with the regression equation Y = 16.723 + 0.501X1, a P-value of 0.000 < 0.05, and an R² value of 21.4%; (2) Understanding of sermons also has a significant effect, with the equation Y = 22.301 + 0.341X1, a P-value of 0.000 < 0.05, and an R² value of 23.6%; (3) The combination of discipline in prayer and understanding of sermons has a simultaneous effect on spiritual intelligence with the model Y = 15.702 + 0.307X1 + 0.234X2, a P-value of 0.000 < 0.05, and an R² value of 29.3%. Therefore, improving discipline in prayer and understanding of sermons can enhance spiritual intelligence.

A recent study analyzed the factors influencing poverty rates in nine cities in East Java from 2020 to 2024, with a specific focus on the unemployment rate, Human Development Index (HDI), and industrial sector growth. Utilizing secondary panel data and a Random Effect Model (REM) for analysis, the research yielded significant insights: higher unemployment positively and significantly correlates with increased poverty, whereas improved HDI levels lead to a significant reduction in poverty. Interestingly, despite growth, the industrial sector's impact on poverty reduction was found to be insignificant. Therefore, policy recommendations stemming from this study highlight the crucial need for proactive measures to curb unemployment, continuous efforts to enhance human resource quality through HDI initiatives, and strategies to ensure industrial growth more directly translate into job creation and improved community well-being..

The purpose of this study is to determine the effect of apparatus competence, internal control and financial systems on fraud prevention in the management of village fund financial reports in Rokan Hulu Regency. In addition, this study also tests individual morality as a moderating variable for the relationship between internal control and financial systems on fraud prevention in the management of village fund financial reports in Rokan Hulu Regency. This research design uses a quantitative approach with the type of primary data that is the sample of village officials from 139 villages in Rokan Hulu Regency. The sample determination was done using the Cluster random sampling technique. The minimum sample in this study was 246. The data analysis technique used in this study uses SEM (Structural Equation Modeling) with the help of IBM-Amos software. The results of this study indicate that internal control and financial systems have an effect on fraud prevention, but the competence of the apparatus does not have an effect on fraud prevention. In addition, individual morality is not able to moderate the effect of the competence of the apparatus and financial systems on fraud prevention. However, it is able to moderate the effect of internal control on fraud prevention.