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This study comprehensively analyzes the impact of sectarian conflict on mental health in Kirkuk through an ethnoreligious meta-analysis of 42 studies with a total of N=15,427 participants published between 2003 and 2023. The quantitative synthesis indicates a PTSD prevalence of 47.3% (95% CI: 44.2–50.4) among victims of sectarian conflict, with an uneven distribution across groups, where the Turkmen minority records the highest prevalence at 56.8%, exceeding Arab Sunni at 43.2% and Kurdish at 41.5%. Logistic regression analysis demonstrates that direct exposure to sectarian violence increases the risk of major depression by 3.4 times (OR=3.42, p<.001), anxiety by 2.8 times (OR=2.83, p<.001), and psychosomatic disorders by 2.5 times (OR=2.54, p<.001). Further meta-regression identifies duration of conflict exposure (β=.426, p<.001) and intensity of sectarian violence (β=.389, p<.001) as significant predictors of symptom severity. In contrast to the findings of Cummings et al. (2013) and Eltally (2019), which emphasize the general impact of conflict, this study reveals specific intergenerational trauma patterns within distinct ethnoreligious communities, with the highest transmission observed among families of sectarian massacre victims (d=0.82), while simultaneously highlighting variations in communal resilience across groups as a differential determinant of post-conflict psychosocial dynamics.

This study examines the dynamic progression of Regional Original Revenue (PAD), the realization of Domestic Investment (PMDN), the size of the labor force, infrastructure availability, and their implications for economic growth across 11 regencies and municipalities in Jambi Province over the period 2017–2023. The analysis employs a panel data regression model, utilizing a combination of time-series and cross-sectional data sourced from Statistics Indonesia and the Regional Investment and One-Stop Integrated Services Office. The empirical findings reveal that PAD experienced a growth rate of 5.39 percent. In contrast, PMDN and the labor force displayed fluctuating patterns, with percentage changes of 905.97 percent and 1.68 percent, respectively. Infrastructure development and economic growth recorded increases of 0.51 percent and 4.04 percent. Further analysis demonstrates that PAD, labor force participation, and infrastructure exert a positive and statistically significant influence on economic growth. Conversely, PMDN does not exhibit a statistically significant effect on regional economic growth within the observed period.

The maritime education sector faces complex challenges in preparing competent seafarers amid the rapid advancement of digital technology. This study investigates the effect of artificial intelligence-based simulations and AI-based competency assessments on competency achievement levels among nautical cadets at Indonesian maritime training institutions. The research design employed a convergent parallel mixed-methods approach, integrating quantitative and qualitative methods to gain a comprehensive understanding. Quantitative data were collected from 150 cadets using a validated questionnaire. In comparison, qualitative data were obtained through in-depth semi-structured interviews with fifteen instructors and ten cadets. Multiple regression analysis revealed that the research model significantly predicted cadet competency achievement. The findings indicate that AI-based assessments exert a stronger influence than AI simulations in improving competency. The qualitative exploration highlighted adaptive feedback mechanisms and personalized learning pathways as critical success factors in implementing learning technologies. This study provides empirical evidence for maritime institutions to prioritize strategic investments in AI-based assessment systems while maintaining a human-centered pedagogy. The research contribution lies in integrating fourth industrial revolution technologies into the training, certification, and watchkeeping standards compliance framework for seafarers, thereby strengthening Indonesia's maritime education ecosystem and aligning it with international standards.

This study aims to: (1) analyze the influence of principal leadership on educational quality at SD Negeri Bimor Jaya, North Morowali; (2) analyze the influence of teacher professionalism on educational quality at SD Negeri Bimor Jaya, North Morowali; (3) analyze the influence of community participation on educational quality at SD Negeri Bimor Jaya, North Morowali; and (4) analyze the simultaneous influence of principal leadership, teacher professionalism, and community participation on educational quality at SD Negeri Bimor Jaya, North Morowali. This research employed a quantitative approach using an associative research design and an ex post facto method. The population of the study consisted of all teachers at SD Negeri Bimor Jaya, all of whom were included as research samples through a total sampling technique. Data were collected using Likert-scale questionnaires and documentation. Data analysis was conducted using descriptive and inferential statistical techniques, preceded by classical assumption tests to ensure the suitability of the regression model. The results of the study indicate that: (1) principal leadership has an influence on educational quality; (2) teacher professionalism has an influence on educational quality; (3) community participation has an influence on educational quality; and (4) principal leadership, teacher professionalism, and community participation simultaneously influence educational quality at SD Negeri Bimor Jaya, North Morowali. These findings emphasize that improving educational quality requires effective school leadership, professional teachers, and active support and involvement from the community.

This study aims to determine the effect of selling price and operational costs on fishermen’s income in Menawi Village, Angkaisera District, Kepulauan Yapen Regency. The population in this study consisted of all fishermen in Menawi Village, Angkaisera District, Kepulauan Yapen Regency. The research sample included 15 fishermen. The data collection technique used in this study was observation through interviews with fishermen, and the data were analyzed using multiple linear regression analysis with the assistance of SPSS 21.0 for Windows. The results of this study indicate that (a) there is a significant simultaneous effect of selling price and operational costs on fishermen’s income in Menawi Village, Angkaisera District, Kepulauan Yapen Regency; (b) there is a positive and significant partial effect of selling price and operational costs on fishermen’s income in Menawi Village, Angkaisera District, Kepulauan Yapen Regency, which can form the basis for economic policy and natural resource management in the fisheries sector. This research is expected to provide insight for policymakers in formulating strategies to increase fishermen's incomes through improved selling prices and more efficient operational cost management.

This study aims to determine the level of income earned by palm sugar (brown sugar) producers in Nubuai Village, Urei Faisei District, Waropen Regency. The research employed a descriptive research design. The population consisted of all palm sugar farmers in Nubuai Village, Urei Faisei District, Waropen Regency. The sampling technique used was purposive sampling, with a total sample of 10 respondents. The data sources included primary and secondary data. Primary data were obtained through direct interviews conducted by the researcher using a structured questionnaire containing previously prepared questions. Secondary data were collected from relevant government institutions related to the study. Data collection techniques included observation, questionnaires, and documentation. Data analysis was carried out using multiple regression analysis, t-test, and F-test. The results showed that the income variable obtained by palm sugar producers had a positive and significant effect on the income of palm sugar farmers in Nubuai Village, Urei Faisei District, Waropen Regency, with a regression coefficient value of Rp 8,976.001 and a significance value of 0.000 < 0.05. The farmers’ revenue variable also had a positive and significant effect on farmers’ income in Nubuai Village, with a regression coefficient value of Rp 15,791.849 and a significance value of 0.038 < 0.05. Furthermore, the variables of experience and palm sugar price simultaneously influenced the income of palm sugar farmers in Nubuai Village, Urei Faisei District, Waropen Regency.

This study seeks to examine the influence of brand image, product innovation, and lifestyle on purchasing decisions for iPhone smartphones among residents of Patumbak Village, Dusun V, Deli Serdang. Specifically, it aims to analyze the individual effect of brand image on purchasing decisions, the effect of product innovation on purchasing decisions, and the effect of lifestyle on purchasing decisions, as well as their combined impact. The research employs a descriptive quantitative approach, utilizing questionnaires, interviews, and documentation as data collection techniques. The population consists of 740 residents of Patumbak Village, Dusun V, and the sample of 88 respondents was determined using non-probability sampling with the Slovin formula. The collected data were processed and analyzed through multiple linear regression analysis using SPSS version 26.0. The findings indicate that the calculated F value (205.841) exceeds the F table value (2.71), demonstrating a significant simultaneous effect of brand image, product innovation, and lifestyle on purchasing decisions. Partially, brand image (t = 2.885), product innovation (t = 2.491), and lifestyle (t = 5.570) each show t-values greater than the t table value (1.662), confirming their significant individual influence. Furthermore, the coefficient of determination (R²) of 0.570 reveals that 57% of the variation in purchasing decisions is explained collectively by the three independent variables.

Mental health is a very important element in supporting students' academic success. As a group at a vulnerable age, students often face academic, social, and psychological pressures that can affect their mental health and academic performance. This study aims to examine the impact of mental health on the academic performance of students at the Faculty of Economics, Pasim National University. The method used in this study is a quantitative approach with data collection through questionnaires. The research subjects consisted of 123 students in their first semester, where the sample included 94 respondents selected using the Slovin formula. The data were analyzed using SPSS software, including validity, reliability, and normality tests, simple linear regression, coefficient of determination, and ANOVA. The findings of this study indicate that all measurement tools used are valid and reliable. Normality testing shows that the data have a normal distribution. The regression analysis results showed a significant positive effect of mental health on students' academic performance. An R-squared value of 0.410 indicates that mental health contributes 41% to the variation in students' academic results, while the remaining 59% is influenced by other factors. The results of the ANOVA also showed a significance level of 0.000 (<0,05). confirming the suitability of the regression model. Therefore, it can be concluded that mental health plays a significant role in improving student academic achievement. This research is expected to provide educational institutions with a basis for designing mental health support policies and programs to improve student academic quality.

The factors influencing lowland rice production in Padang City are the focus of this study. The study was conducted through a field survey of lowland rice farmers to obtain primary data relevant to farming activities. The analysis method used was multiple linear regression with the dependent variable being lowland rice production (Y) and independent variables including land area (X₁), seeds (X₂), fertilizer (X₃), labor (X₄), and farming experience (X₅). The research findings show that simultaneously all production factors, including land area, seeds, fertilizer, labor, and farming experience, have a significant effect on lowland rice production in Padang City. Partially, the variables of fertilizer and labor have a significant effect on lowland rice production, while land area, seeds, and farming experience have no significant effect. These findings indicate that the increase in lowland rice production in Padang City is more determined by input intensification efforts, particularly through appropriate fertilization and labor availability, compared to land expansion. As a result, agricultural policies need to be directed at increasing input efficiency to support the productivity and sustainability of rice farming.

This study examines the influence of work experience, knowledge, education, and leadership policies on the implementation of PSAK 109 for Zakat, Infaq, and Sadaqah accounting at Zakat Management Bodies in Pontianak City and Kubu Raya Regency, West Kalimantan. Although PSAK 109 is essential for ensuring transparency and accountability in zakat fund management, its implementation remains suboptimal in practice. A quantitative survey was conducted by distributing questionnaires to zakat officers (amil) at BAZNAS and Zakat Collection Units. Using purposive sampling, the data were analyzed through validity, reliability, classical assumption tests, and multiple linear regression. The findings reveal that work experience, knowledge, and leadership policies significantly and positively affect PSAK 109 implementation, while education does not show a significant effect. Collectively, all variables have a significant influence. The study concludes that practical competence, technical understanding, and supportive internal policies are more crucial than formal education. Strengthening training and leadership policies is recommended to enhance accountability and transparency.  

This study analyzes the impact of learning motivation levels on student attendance discipline at the Saint Ignasius Catholic Vocational School in Wairterang. The background of the problem highlights the low level of student attendance, which is caused by the lack of intrinsic and extrinsic motivation in the vocational education environment. This phenomenon impacts the effectiveness of learning and overall student achievement. The purpose of the study is to identify the causal relationship between learning motivation and attendance discipline, and to measure the significant influence of motivation variables on attendance discipline. The approach used is quantitative with a Likert-scale questionnaire survey method. The study sample involved students in grades X-XII at the Saint Ignasius Catholic Vocational School in Wairterang, with data analysis using simple linear regression to test the hypothesis. The results of the study are expected to show a positive and significant influence of learning motivation on attendance discipline. Practical implications include recommended strategies for guidance and counseling (BK) teachers, such as individual counseling programs, attendance-based reward systems, and the integration of intrinsic motivation through vocational extracurricular activities. These strategies are expected to improve learning effectiveness and build students' disciplined character in vocational high schools

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.

The rapid growth of e-commerce has intensified competition among digital businesses, making pricing and discount strategies critical in influencing consumer purchase decisions. This study aims to examine the effect of original product price and price after discount on consumer purchase decisions on e-commerce platforms. A quantitative causal research design was employed using secondary data derived from publicly available e-commerce transaction records. Data analysis was conducted through descriptive statistics, correlation analysis, and multiple linear regression to assess the partial and simultaneous effects of pricing variables on purchase decisions, which were measured using a price-based purchase decision index. The findings indicate that both original price and discounted price have a significant negative effect on consumer purchase decisions. This suggests that lower displayed and final prices increase consumers’ likelihood of making a purchase. Furthermore, the discounted price was found to exert a more dominant influence than the original price, highlighting the importance of perceived value in online purchasing behavior. This study contributes to the digital marketing literature by providing empirical evidence on pricing effects in e-commerce and offers practical insights for e-commerce platforms in designing effective and data-driven pricing and discount strategies.

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.

This study explores the influence of Electronic Word of Mouth (E-WOM) on Umrah ticket purchasing decisions through the Instagram account @umrohbarengyuk.id. In today’s digital era, social media serves as a primary channel in shaping consumer perceptions of services, particularly in religious travel industries like Umrah. E-WOM, consisting of interaction intensity, opinion valence, and content quality, plays a vital role in providing trustworthy information and building consumer confidence. Using a quantitative method involving surveys and simple linear regression analysis, the study finds that digital reviews and testimonials strongly influence prospective pilgrims’ decisions. The @umrohbarengyuk.id account is perceived as providing transparent, responsive, and relevant communication, making it a key reference in users’ information-seeking and service evaluation processes. These findings reinforce E-WOM as a powerful digital marketing communication strategy that not only increases service appeal but also enhances customer trust and purchasing confidence. The study offers practical insights for Umrah service providers in developing personalized, credible digital content and strategies to reach broader audiences effectively.

This study aims to compare the performance of Multiple Linear Regression (MLR) and Random Forest Regression (RFR) in predicting student performance based on academic scores. Student performance is defined as the average of math scores, Reading Scores, and writing scores. This study uses a quantitative approach with a comparative design based on predictive modeling. The data used is secondary data from the Student Prediction dataset obtained through the Kaggle platform, which was processed using the Python programming language through the Google Colab platform. The analysis stages included the formation of performance variables, the separation of training and test data with a ratio of 80:20, model training, and evaluation using the Mean Squared Error (MSE), Mean Absolute Error (MAE), and coefficient of determination (R²) metrics. The results show that the Multiple Linear Regression model produced an MSE value of 2.74 × 10⁻²⁸, an MAE of 1.51 × 10⁻¹⁴, and an R² of 1.000. Meanwhile, Random Forest Regression produced an MSE of 0.296, an MAE of 0.375, and an R² of 0.998. These findings indicate that both models have a very high level of accuracy, but Multiple Linear Regression provides the best performance. This is due to the strong linear relationship between the input variables and the target variables formed directly from the combination of academic values. Thus, the linear regression model is proven to be more suitable for use in data structures that have simple linear relationships compared to ensemble-based models.

Students’ learning motivation is a crucial factor in determining the success of the learning process in schools and is influenced by various external factors, including teacher competence and learning facilities. Teachers with adequate competence are able to manage learning activities effectively, while sufficient learning facilities create a conducive environment that supports student engagement and enthusiasm for learning. This study aims to analyze the effect of teacher competence and learning facilities on students’ learning motivation at SMA Islam Al-Munir Bekasi City. This research employed a quantitative method with an associative approach. The research population consisted of all eleventh and twelfth-grade students of SMA Islam Al-Munir Bekasi in the 2024/2025 academic year, totaling 55 students. A saturated sampling technique was applied, in which the entire population was used as the research sample. Data were collected through questionnaires distributed to respondents and supported by interviews, observations, and documentation. The collected data were analyzed using multiple linear regression analysis with the assistance of SPSS software. The results indicate that teacher competence has a positive and significant effect on students’ learning motivation, meaning that higher levels of teacher competence in pedagogical, professional, personal, and social aspects lead to increased student motivation. In addition, learning facilities also have a positive and significant effect on students’ learning motivation, showing that adequate learning infrastructure and facilities are able to enhance students’ interest and enthusiasm for learning. Simultaneously, teacher competence and learning facilities have a significant effect on students’ learning motivation at SMA Islam Al-Munir Bekasi City. The implications of this study emphasize the importance of continuous efforts by schools to improve teacher competence and to provide and maintain adequate learning facilities in order to create a more effective learning process and to strengthen students’ learning motivation.

A student's learning success is largely determined by their academic evaluation. Estimating a student's final grade can assist educational institutions in conducting initial assessments of academic achievement. This study aims to analyze the performance of the Multiple Linear Regression (MLR) and Random Forest (RF) algorithms in predicting students' final grades using Google Colab. This research method uses a quantitative approach using secondary data that includes age, mid-term exam scores, final exam scores, and categorical variables as independent variables, with the final grade as the dependent variable. The research process is carried out through data preprocessing steps, dividing training and test data, model training, and performance evaluation using Mean Squared Error (MSE), Mean Absolute Error (MAE), and the coefficient of determination (R2). The results show that the Random Forest algorithm provides more accurate prediction accuracy compared to the Multiple Linear Regression algorithm, especially in identifying nonlinear relationships between variables. Therefore, the Random Forest algorithm is more recommended for predicting students' final grades with complex data characteristics.

This study analyzes the impact of learning motivation levels on student attendance discipline at the Saint Ignasius Catholic Vocational School in Wairterang. The background of the problem highlights the low level of student attendance, which is caused by the lack of intrinsic and extrinsic motivation in the vocational education environment. This phenomenon impacts the effectiveness of learning and overall student achievement. The purpose of the study is to identify the causal relationship between learning motivation and attendance discipline, and to measure the significant influence of motivation variables on attendance discipline. The approach used is quantitative with a Likert-scale questionnaire survey method. The study sample involved students in grades X-XII at the Saint Ignasius Catholic Vocational School in Wairterang, with data analysis using simple linear regression to test the hypothesis. The results of the study are expected to show a positive and significant influence of learning motivation on attendance discipline. Practical implications include recommended strategies for guidance and counseling (BK) teachers, such as individual counseling programs, attendance-based reward systems, and the integration of intrinsic motivation through vocational extracurricular activities. These strategies are expected to improve learning effectiveness and build students' disciplined character in vocational high schools

This research aims to see the effect of Total Asset Turnover and Debt To Equity Ratio (DER) on Return On Assets (ROA) at PT Indofood Sukses Makmur Tbk which is listed on the BEI in 2010 - 2023. The data used in this research is data secondary in the form of the annual financial report of the company under study. This research uses quantitative data and the data source used is secondary data with an analysis method using multiple linear regression methods with data processing using SPSS v.25. The results of hypothesis testing (T Test) partially state that the Total Asset Turnover variable does not have a significant and positive influence on Return On Assets (ROA) and the Debt To Equity Ratio (DER) variable has a significant and negative influence on Return On Assets (ROA). Simultaneous F Test results of the Total Asset Turnover and Debt To Equity Ratio (DER) variables show a significant influence between Total Asset Turnover and Debt To Equity Ratio (DER) on Return On Assets (ROA).