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This study aims to determine the extent to which motivation and work discipline affect employee productivity at CV. Langgeng Jaya. The study uses a quantitative descriptive approach with data collection techniques through distributing questionnaires. The study population includes all 80 employees of CV. Langgeng Jaya, with a sampling technique using Saturated Sampling. Data analysis was carried out through Multiple Linear Regression Tests and Hypothesis Tests with the help of the SPSS 27 program. The results of the study indicate that motivation has a significant influence on employee productivity partially, while work discipline does not have a significant influence. However, simultaneously, motivation and work discipline have been proven to have a significant influence on employee productivity. Therefore, CV. Langgeng Jaya is expected to prioritize increasing employee motivation through targeted programs and conducting evaluations and coaching on work discipline aspects, so that both factors can support each other in increasing overall productivity. This aims so that both factors can support each other in increasing overall employee productivity, creating a more productive work environment, and improving company performance in the long term.

Income inequality and poverty continue to be major challenges in Indonesia's industrial areas, especially in DKI Jakarta, West Java, and Banten, although minimum wage policies continue to be developed as a form of protection for low-income workers. These policies theoretically serve as an instrument for income redistribution and improvement of labor welfare, but their effectiveness in reducing inequality and reducing poverty rates is still questionable, especially in areas with highly industrialized economic structures. This study aims to analyze the influence of income inequality, poverty rate, economic growth, and unemployment rate on the dynamics of the provincial minimum wage in the 2016–2023 period. The study used secondary data obtained from the Central Statistics Agency and analyzed using panel data regression to obtain a comprehensive empirical picture of the factors determining the minimum wage. The test results show that the Fixed Effect Model is the most suitable model for capturing variations between provinces and between times. Key findings reveal that poverty levels and economic growth have a significant influence on changes in the minimum wage, while income inequality and unemployment rates have no significant influence. The conclusion of the study emphasizes that the minimum wage policy is not effective enough in reducing income inequality and reducing poverty without the expansion of the formal sector, improving the quality of the workforce, and distributing economic growth more evenly between industrial areas.

This study analyzes the influence of Islamic business ethics principles on online buying and selling transactions in the predominantly Muslim community of South Sumatra. Using a quantitative approach through a survey of 200 respondents in Palembang with a Likert scale questionnaire, the data were analyzed using multiple linear regression with SPSS 26. The results showed that the principle of honesty (sidq) had the strongest significant influence (β = 0.029, p = 0.002), followed by unity (tawhid) (β = 0.016, p = 0.049), while other principles such as balance, free will, and responsibility showed a positive but insignificant influence. The regression model explained 10.3% of the variation in transaction behavior (R² = 0.103). This study concluded that the application of Islamic ethics can increase trust and sustainability in e-commerce in the region, with implications for the development of halal businesses. In the future, the application of these principles is expected to mitigate ethical issues in e-commerce, such as fraud and uncertainty that often occur, as well as strengthen transparency and fairness in online transactions.

This study analyzes the impact of artificial intelligence on youth digital political engagement through a Structural Equation Modeling approach. The development of algorithmic technology has changed the way young people access, assess, and react to political information, requiring an empirical understanding of its mechanisms of influence. This study explores how digital literacy, trust in AI, and perceived usefulness shape online political participation. Data was obtained from an online questionnaire targeting individuals aged 17-30 who are active with AI, then analyzed using the SEM-PLS 4 method. The main findings reveal that digital literacy and trust in AI have a strong influence on perceived usefulness, which acts as a key mediator in encouraging such participation. This indicates that the impact of AI is not direct, but rather occurs through cognitive processes that guide young people in assessing the benefits of technology. The implications of this research emphasize the importance of strengthening digital literacy, algorithm transparency, and responsible AI implementation to strengthen inclusive youth political participation in the digital environment.

Abortion remains a complex reproductive health issue due to the interplay of multiple interrelated determinants. This study aimed to map the factors influencing the incidence of abortion based on recent scientific evidence. A literature review design was applied by analyzing ten selected articles published within the last five years and retrieved from major scientific databases. The selection process was conducted systematically through title, abstract, and full-text screening based on predefined inclusion criteria. The extracted data included study characteristics, type of abortion, examined determinants, and key conclusions. The synthesized findings indicate that abortion incidence is shaped by a combination of biological, social, and healthcare system related factors. Clinical determinants such as maternal age, endocrine disorders, uterine anatomical abnormalities, obstetric history, anemia, and hypertension play a substantial role in spontaneous and recurrent miscarriage. In contrast, structural factors including income level, contraceptive access, and legal regulations predominantly influence induced abortion. The discussion highlights that abortion should not be viewed as an isolated clinical event, but rather as the cumulative outcome of risks operating across multiple levels of influence. In conclusion, abortion represents a multifactorial phenomenon that requires comprehensive prevention strategies extending beyond medical interventions alone. These strategies should also address healthcare accessibility and broader social conditions. This review contributes to a deeper understanding of the complexity of abortion determinants and provides an evidence-based reference for developing more effective preventive approaches in the future.

This study aims to examine the effect of Environmental, Social, and Governance (ESG) disclosure, Return on Assets (ROA), and Enterprise Resource Planning (ERP) on tax avoidance in energy sector companies listed on the Indonesia Stock Exchange during the 2021–2024 period. This research employs a quantitative approach using secondary data obtained from annual reports and sustainability reports. The sample was selected using a purposive sampling technique, resulting in 112 observations. Multiple linear regression analysis was conducted using Stata 16 software. The empirical results indicate that ESG, ROA, and ERP simultaneously have no significant effect on tax avoidance. Partially, each independent variable also shows no significant influence. These findings suggest that ESG implementation and ERP adoption have not directly affected corporate tax behavior, while profitability is not a primary determinant of tax avoidance in the energy sector. This study contributes to the existing literature by incorporating ERP as a novel variable in tax avoidance research, providing additional insight into the role of integrated information systems in corporate taxation practices.

This study aims to analyze the factors influencing the income levels of pineapple farmers in Siabal-Abal V Village, Sipahutar Subdistrict, North Tapanuli Regency. The research focuses on several key variables, namely land size, production quantity, production tools, and farming experience, which are presumed to be associated with farmers’ income. A quantitative research approach was employed, using multiple linear regression analysis to examine the simultaneous and partial effects of each variable on the income of pineapple farmers. The population of this study comprised all pineapple farmers in Siabal-Abal V Village, with a sample of 65 respondents selected through a simple random sampling technique. Data were collected through interviews and structured questionnaires designed in accordance with the research objectives. The results of the data analysis indicate that, simultaneously, land size, production quantity, production tools, and farming experience have a significant effect on the income of pineapple farmers. However, the partial test results reveal that only land size has a positive and significant effect on farmers’ income. Meanwhile, production quantity, production tools, and farming experience do not show a statistically significant influence. These findings indicate that land size is the dominant factor in determining the income level of pineapple farmers in the study area. Therefore, improving access to agricultural land or optimizing the utilization of existing land is an important strategy for increasing the income of pineapple farmers in Siabal-Abal V Village.

This study aims to analyze the effect of asset growth, capital structure, and asset structure on the profitability of PT Astra Graphia Tbk during the period 2016–2023. The research employs a quantitative approach with a causal research design using secondary data derived from the company’s quarterly financial statements. A total of 32 quarterly observations were selected through purposive sampling. Profitability is measured using Return on Equity (ROE), while data analysis is conducted using multiple linear regression. Prior to hypothesis testing, classical assumption tests including normality, multicollinearity, heteroskedasticity, and autocorrelation tests were performed to ensure the robustness of the regression model. The results indicate that asset growth, capital structure, and asset structure simultaneously have a significant effect on firm profitability. However, partially, only asset structure has a significant effect on profitability, while asset growth and capital structure show no significant influence. These findings suggest that efficient asset composition plays a more critical role in improving profitability than mere asset expansion or increased leverage. The managerial implication of this study highlights the importance of optimizing asset structure to enhance the firm’s ability to generate sustainable profits.

This study examines the influence of good governance principles on village fund utilization effectiveness in Indonesia. Using a quantitative approach with Structural Equation Modeling - Partial Least Squares (SEM-PLS), we analyze data from 385 village officials across five provinces in Indonesia. The research integrates stewardship theory and agency theory to explain how transparency, accountability, participation, and rule of law affect village fund management performance. Results demonstrate that transparency (β=0.342, p<0.01) and accountability (β=0.287, p<0.01) significantly enhance village fund utilization effectiveness, while participation (β=0.219, p<0.05) shows moderate influence. Rule of law (β=0.156, p>0.05) does not significantly affect fund utilization, suggesting implementation challenges. The model explains 68.4% variance in village fund utilization effectiveness (R²=0.684). This study contributes to governance literature by providing empirical evidence from emerging economies and offers practical implications for policymakers to strengthen village-level financial management through enhanced transparency mechanisms and accountability systems. The findings highlight the critical role of good governance in achieving sustainable rural development goals.

Negative Binomial Regression is a statistical modeling approach used to analyze count data with overdispersion, where the variance exceeds the mean. This study applies the method to examine the influence of weather factors on the daily number of cyclists crossing the Williamsburg Bridge in New York City. The independent variables used in the analysis include maximum temperature, minimum temperature, and precipitation. The dataset was obtained from the NYC Department of Transportation through the Kaggle platform and covers the period from April 1 to April 30, 2016. The analysis began with a Poisson Regression model; however, the presence of overdispersion was identified, indicated by a high AIC value of 8598.19, suggesting that the model was not suitable. The alternative Negative Binomial Regression model was then employed and produced a significantly lower AIC value of 518.77, demonstrating a superior fit. The findings indicate that maximum temperature has a positive effect on the number of cyclists, while precipitation shows a significant negative effect. Conversely, minimum temperature does not exhibit a meaningful influence. These results highlight the importance of considering weather conditions when planning bicycle-based transportation systems and support the development of sustainable mobility strategies in urban environments.

Balikpapan City, as one of the economic centers in East Kalimantan, plays an important role in the development of Micro, Small, and Medium Enterprises (MSMEs). The Goetji, as one of the MSMEs engaged in the beverage industry, faces significant challenges and opportunities in improving its performance and competitiveness. This study aims to analyze the influence of employee work motivation, corporate culture, and corporate atmosphere on business production and economic growth in Balikpapan City. The research method used is a quantitative approach with statistical analysis to measure the relationship between the variables studied. Data was collected through a survey involving The Goetji employees and analyzed using regression analysis to identify the significance of each factor's influence. The results show that employee motivation has a significant effect on the development of The Goetji SMEs, with a significance value of 0.000, indicating a strong relationship. In addition, a positive corporate culture and a supportive corporate atmosphere also contribute to increased productivity and product quality. This positive impact is not only seen in The Goetji's internal performance but also contributes to local economic growth by creating jobs and increasing regional income. This study concludes that strengthening work motivation and a positive corporate culture are key to improving the performance of MSMEs, which in turn contributes to the economic growth of Balikpapan City. Recommendations are provided to continue developing strategies that support these two aspects in order to achieve greater sustainability and growth

This paper applies the Gamma Regression Model to determine the probability of newborns in the Diyala Province developing neonatal jaundice, or hyperbilirubinemia. This disease is prevalent, and it may be severe due to the large amount of unconjugated bilirubin in the blood. The aim of the study was to test the relationship between the levels of bilirubin and a set of independent variables, including the weight of birth, gestational age, and the proportion of red blood cells (PVC). 67 worth of data regarding neonatal cases was collected, and the outcome was that the model fitted well. The findings further indicated that whereas the influence of PVC was significant and positive on the bilirubin level, lower gestational age and less weight at birth had significant negative influence. As the results of the study indicate, the Gamma Regression Model is an effective tool to assess medical data and predict critical scenarios, which assists a clinician with the timely and accurate decision-making.

This study analyzes the factors leading to academic fraud among accounting students, focusing on the predictive power of the Fraud Hexagon Theory and intellectual intelligence. It also investigates the role of student ethical behavior as a moderating variable. Using a quantitative approach, data was collected from 111 respondents selected through purposive sampling. The data was subsequently analyzed using SPSS version 25. The findings revealed that the Fraud Hexagon model was only partially validated. Three of its six dimensions emerged as significant predictors of academic fraud: rationalization, capability, and opportunity. Conversely, pressure, ego, and collusion showed no significant influence. The study also found no statistical relationship between a student's intellectual intelligence and their tendency to commit fraud. Furthermore, student ethical behavior did not effectively moderate the influence of the significant Fraud Hexagon factors. The study concludes that academic fraud is a complex phenomenon primarily triggered by internal justification, individual capabilities, and external opportunities. The lack of correlation with intellectual intelligence suggests that cognitive ability is not an inherent barrier to dishonest acts. These findings underscore that a strong ethical character is the most powerful safeguard against fraud, highlighting the irreplaceable role of ethics education in fostering academic integrity.

The development of the digital economy has driven major changes in consumer behavior, from traditional transactions to online interactions. These changes present both challenges and opportunities for businesses, particularly in the e-commerce sector, where consumer trust, data privacy, and digital technology adoption are important factors in decision-making. This study aims to map global trends in online consumer behavior research in the context of the digital economy using bibliometric analysis. Data was collected from the Scopus database using the keyword “online consumer behavior” for the period 2020-2025. The dataset was exported in CSV format and analyzed using VOSviewer and R Studio (Biblioshiny). The analysis included annual publication trends, identification of authors, journals, countries, as well as keyword mapping and citation networks. The results show a significant increase in publications after 2020, with China, the United States, and India as the main contributors. Keyword mapping reveals four research clusters: consumer trust and data privacy, e-commerce and digital platform adoption, consumer experience and personalization, and social commerce and social media influence. These findings confirm a growing research focus on issues of digital trust and opportunities for utilizing new technologies such as artificial intelligence and social media. This study provides a comprehensive overview of global trends in online consumer behavior and an important contribution to academics, practitioners, and policymakers.

This study aims to analyze the factors influencing GoPay user loyalty in Semarang. The background of this research is based on the high penetration of e-wallet services in Indonesia, which is increasingly competitive, with many service providers such as OVO, DANA, ShopeePay, and LinkAja offering various promotional programs. The research method used a quantitative approach through a survey of 120 active GoPay user respondents, then the data was analyzed using the SmartPLS application. The results showed that promotions did not significantly influence user loyalty, while perceptions of usefulness and brand image had a positive and significant influence. This indicates that user loyalty is not only built through short-term incentives, but is more determined by perceptions of service benefits and trust in the brand image. These findings emphasize the importance of companies not only relying on promotional strategies, but rather focusing more on improving service quality, feature innovation, and consistency in maintaining brand reputation. With the right strategy, GoPay is expected to maintain a loyal user base amidst the increasingly fierce e-wallet competition in Indonesia.

Rapid technological advancements have encouraged smartphone sellers to emphasize good product quality to meet customer needs in order to achieve customer satisfaction and repurchase intentions. A positive brand image and good perceived value are important factors in building customer satisfaction, which ultimately impacts repurchase intentions. This study aims to examine the influence of product quality, brand image, and perceived value on customer satisfaction and thus increasing repurchase intentions. The study was conducted in Jakarta with a descriptive causality design through a quantitative approach and purposive sampling technique. Data were obtained from 131 respondents who have used an iPhone. The conceptual model analysis was conducted using the Structural Equation Modeling method. The results show that product quality, brand image, and perceived value significantly increase customer satisfaction. Furthermore, customer satisfaction has been shown to encourage repurchase intentions. In addition, product quality, brand image, and perceived value each have a positive influence on repurchase intentions through the mediation of customer satisfaction. Thus, all hypotheses of this study are proven to have a positive influence. The contribution of this research is expected to provide understanding for producers in developing their business, as well as being a reference for developing marketing strategies that emphasize improving product quality, building a strong brand image, managing value perceptions, and increasing customer satisfaction in order to attract consumer interest in repeating the same product.

This study aims to examine the influence of ratings and influencer marketing on purchasing decisions for skincare products on the Shopee marketplace. This quantitative study involved 96 respondents and used multiple linear regression data analysis. The results show that ratings and influencer marketing have a significant influence. Purchasing decisions are influenced by ratings, which is the most dominant variable, meaning that the higher the rating, the greater the interest in the product. These findings emphasize the importance for sellers to maintain product and service quality to maintain high ratings and to collaborate with credible influencer marketers to strengthen their marketing strategies.

Net profit is an important indicator in assessing a company's financial performance because it reflects the effectiveness of management in generating profits. Several factors that influence net profit include sales, cost of goods sold, operating expenses, and other income. This study aims to analyze the influence of these factors on net profit at PT. Pesona Minuman Indonesia during the 2021–2023 period. The independent variables include sales, cost of goods sold, operating expenses, and other income, while net profit serves as the dependent variable. A quantitative approach using multiple linear regression was applied to 36 quarterly data from the company. The results show that sales, cost of goods sold, and operating expenses have a positive and significant influence on net profit, while other income has a negative and significant influence. Simultaneously, all four variables have a significant influence on the company's net profit. This finding emphasizes the importance of good management of sales and operating costs as key factors in achieving optimal profitability. Therefore, the company needs to focus on increasing sales and controlling operating costs to maximize its net profit.

This study analyzes the effect of Total Asset Turnover, Debt to Equity Ratio, and Return on Assets on earnings management in mining companies listed on the Indonesia Stock Exchange during 2020–2024. Using a quantitative and causal research design, the study examines 18 purposively selected companies over five years, resulting in 90 observations. Data were analyzed through panel data regression using SPSS 26. The results show that Total Asset Turnover does not significantly affect earnings management, while Debt to Equity Ratio and Return on Assets have a significant influence. These findings indicate that profitability and leverage play important roles in shaping earnings management practices in the mining sector

This study aims to analyze the influence of product quality (X1), price (X2), and location (X3) on consumer satisfaction (Y) at UMKM Abon Farda Kediri. The research uses a quantitative approach with both primary and secondary data. The sample consists of 64 respondents, and the data were collected through questionnaires, literature reviews, and documentation. The analytical methods applied include Validity Test, Reliability Test, Classical Assumption Test, Multiple Linear Regression Analysis, t-test, F-test, and the Coefficient of Determination test. The results of the analysis show the multiple linear regression equation: Y = 5.464 + 0.297X1 + 0.280X2 + 0.165X3 + e. Based on the t-test, the product quality variable has a t-value of 2.132 with a significance level of 0.037, indicating a significant effect on consumer satisfaction. The price variable has a t-value of 2.284 with a significance level of 0.026, also showing a significant influence. However, the location variable records a t-value of 1.176 with a significance level of 0.244, meaning it does not significantly affect consumer satisfaction. The F-test results show an F-value of 8.223 with a significance level of 0.000, confirming that product quality, price, and location simultaneously have a significant effect on consumer satisfaction. Therefore, product quality and price play an important role in increasing consumer satisfaction at UMKM Abon Farda Kediri.