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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 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

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.

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 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.

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.

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.

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.

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.

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 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.

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).

Ideally, final-year undergraduates are expected to demonstrate psychological maturity and a clear sense of future direction. However, the pressure of academic demands and social expectations often precipitates a "quarter-life crisis," triggering profound anxiety during this transitional phase. This study investigates the relationship between religiosity and the quarter life crisis among final-year students at Universitas Ibrahimy Situbondo. Employing a quantitative correlational design, the study involved 149 students selected via convenience sampling from a population of 237. Data were collected using the Religiosity Scale and the Quarter-Life Crisis Scale, then analyzed using simple linear regression with JASP version 0.19.1.0. Contrary to common assumptions in religious settings, the findings revealed that religiosity was not significantly associated with the quarter life crisis (p = .105 > .05). The effective contribution of religiosity in explaining the variance of the crisis was minimal (R2 = 0.018 or 1.8%), indicating that 98.2% of the phenomenon is driven by factors outside the scope of this study. These results suggest that religiosity is not a sole predictor capable of buffering against quarter life crisis. Consequently, further research should explore other potential mitigating variables, such as social support, self-efficacy, or career adaptability, particularly within Islamic boarding school-based university environments.

The auditor's responsibilities include not only assessing the accuracy of financial statements and detecting fraud, but also evaluating the company's ability to continue its business on an ongoing basis. This responsibility arises from the expectations of shareholders and other stakeholders that auditors provide timely and relevant information about the company's future prospects to support rational and evidence-based investment decision-making. In this context, audit opinions related to business continuity are an important instrument in reducing information asymmetry between management and investors. This study aims to analyze the impact of liquidity, solvency, and audit quality on the issuance of business continuity declarations. The research sample consisted of coal mining companies listed on the Indonesia Stock Exchange between 2014 and 2017, a period marked by fluctuations in commodity prices and global economic uncertainty. Logistic regression is used as an analysis method because dependent variables are dichotomous. The results showed that audit quality had a significant negative impact on the issuance of business continuity declarations, while liquidity and solvency did not have a significant impact on the issuance of the declarations, indicating that the factors of governance and auditor independence were more decisive than short-term financial conditions.

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.

As HIV transitions into a manageable chronic condition, optimizing lifestyle behaviors is key to achieving long-term health outcomes. This study aims to explore lifestyle behaviors in people with HIV (ODHIV) who participate in peer support groups as well as identify socioeconomic and clinical predictors of healthy lifestyle engagement. The research design was a cross-cutting analysis involving 250 ODHIV registered in a community support group. Lifestyle behavior was measured using  a modified Health-Promoting Lifestyle Profile II (HPLP-II) instrument. Multivariate logistic regression analysis was used to determine independent predictors, with Nagelkerke R² and Hosmer–Lemeshow tests  to assess model suitability. The results showed that 56.2% of respondents had a healthy lifestyle. Factors of higher education (OR = 2.77; p = 0.006), older age (OR = 2.32; p = 0.015), employment status (OR = 2.00; p = 0.029), and longer duration of ART therapy (OR = 1.17 per year; p = 0.003) were significant predictors. The model explains 32% of lifestyle variations, with ART compliance and substance control as the strongest behavioral domains. These findings confirm the role of peer support groups as a behavioural reinforcement environment, but socioeconomic disparities remain influential. The integration of theory-based lifestyle interventions into community-based HIV services is necessary to optimize chronic disease outcomes.

Delays in the submission of audited financial reports (audit report lag) remain a problem for public companies in Indonesia because they can reduce the relevance of information for investors and stalk holders. This study aims to analyze the effect of profitability, solvency, liquidity, operational complexity, and company size on audit report lag in property and real estate companies listed on the Indonesia stock exchange for the period 2022-2024. The research method used is quantitative with panel data regression analysis using Random Effect Model (REM). The results show that profitability and solvency have a negative effect on audit report lag, while company size have no effect. Simultaneously, all independent variables affect audit report lag. This study emphasizes the importance of financial performance and operational complexity in determining the timeliness of audited financial reporting.

This study aims to analyze the effect of company size and profitability on tax avoidance in manufacturing companies listed on the Indonesia Stock Exchange (IDX) during the 2022–2024 period. The research uses secondary data obtained from published financial statements, with a sample of 333 companies selected through a purposive sampling technique. Panel data regression is employed as the main analytical method to examine the relationship between the independent variables and tax avoidance practices. The results of the analysis indicate that profitability has a positive and significant effect on tax avoidance, suggesting that more profitable companies tend to engage more actively in tax planning strategies to reduce tax burdens. In contrast, company size is found to have no significant effect on tax avoidance, indicating that large and small manufacturing firms exhibit similar tax behavior. Overall, this study provides empirical evidence regarding the determinants of corporate tax avoidance and contributes to the literature by offering insights for policymakers, regulators, and stakeholders in understanding tax avoidance behavior in the manufacturing sector.

This research aims to: 1) examine the development of the Human Development Index (HDI), Labor Force Participation Rate (LFPR), population size, economic growth, and the poverty gap index in the regencies/cities of Jambi Province from 2020 to 2024; and 2) analyze the influence of the Human Development Index, Labor Force Participation Rate, population size, and economic growth on the poverty gap index in the regencies/cities of Jambi Province. The research method employed is descriptive quantitative. The analytical tool used is Panel Data Regression through the Fixed Effect Model (FEM) approach, processed with EViews 12 software. The results show that the Human Development Index, population size, and economic growth have a significant influence on the poverty gap index in the regencies/cities of Jambi Province during the 2020-2024 period. Conversely, the LFPR does not have a significant effect on the poverty gap index in the region during the same period. These findings imply the importance of strengthening human resource quality through HDI improvement and more inclusive economic growth policies in Jambi Province. Furthermore, the government needs to evaluate the quality of available employment, as the high Labor Force Participation Rate (LFPR) has not yet been able to significantly reduce the depth of poverty.

Stroke is one of the non-communicable diseases that is the leading cause of disability and death in the world. Clinical factors such as hypertension, diabetes mellitus, body mass index (BMI), and unhealthy lifestyle are known to contribute to the incidence of stroke. Oe-Cusse Referral Hospital serves as the main referral center in the treatment of stroke cases, but data on contributing clinical factors and medical treatment and rehabilitation strategies are still limited. This study aims to analyze the clinical factors that contribute to the incidence of stroke and describe medical treatment and rehabilitation strategies in stroke patients at Oe-Cusse Referral Hospital.This study is a quantitative study with a cross-sectional observational design. The research sample amounted to 50 stroke patients who were treated in the January-November 2025 period, selected using purposive sampling techniques. Data were collected through medical records and questionnaires related to medical treatment and rehabilitation. Data analysis was carried out using the SPSS program, including descriptive analysis and logistic regression to see the relationship between clinical factors (hypertension, diabetes mellitus, lifestyle, BMI, and other factors) and stroke incidence. The results of the descriptive analysis showed that the average age of stroke patients was 56.2 ± 9.8 years, with an age range of 39–78 years. The average BMI of the patient was 27.5 ± 3.1 kg/m² which indicates a tendency to be overweight. The average systolic blood pressure of the patient was 150 ± 18 mmHg, indicating the predominance of hypertension in stroke patients. The average length of rehabilitation lasted 6.3 ± 1.8 weeks. Logistic regression analysis showed a significant relationship between clinical factors, especially hypertension, BMI, and diabetes mellitus, and stroke incidence. Clinical factors such as hypertension, high BMI, and diabetes mellitus contribute significantly to the incidence of stroke at Oe-Cusse Referral Hospital.