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This study aims to determine the effect of the physical work environment and work motivation on the performance of employees of PT Pancaran Indonesia Kabupaten Tangerang, Depok City, both partially and simultaneously. The method used is a quantitative method with a causal associative approach and probability sampling technique with a sample of 82 and processed using SPSS 25. Data analysis using validity test, reliability test, classic assumption test, regression analysis, correlation coefficient analysis, coefficient of determination analysis, and hypothesis testing. The results of the study show that the physical work environment has a value of tcount > ttable or (3,714 > 1.994). Work motivation has a tcount > ttable or (11,852 > 1.994). The physical work environment and work motivation have Fcount > Ftable or (72, 865 > 2,737). This is also reinforced by the ρ value < Sig.0.05 or (0.000 <0.05). there is a significant effect simultaneously between the physical work environment (X1) and work motivation (X2) on employee performance (Y) with a contribution of 67,9% while the remaining 32,1% is influenced by other factors outside this study. The multiple linear regression equation Y = 5,949 + 0,067X1 + 0,985X2 + e.

The rapid development of information technology has transformed social media into a digital space that plays a crucial role in shaping the mindset, behavior, and lifestyle of young generations. TikTok is one of the most dominant platforms used by Generation Z, particularly students, due to its ability to present algorithm-based content that aligns with user interests. This condition has the potential to cause psychological stress in the form of Fear of Missing Out (FOMO), which reflects social anxiety due to the perception of being late in keeping up with trends, information, or experiences that hold a dominant position in the social landscape. This research initiative aims to examine the influence of TikTok usage on the lifestyle configurations of Generation Z students, with FOMO serving as a determinant that strengthens this relationship. This study is designed within the quantitative tradition with a positivist epistemological orientation. The study population includes 250 students from the Faculty of Computer Science at the National Pasim University in Bandung, with a sample size of 72 respondents derived using Slovin's formula. The analysis results indicate that TikTok usage and the level of FOMO have a positive and significant impact on changes in students' lifestyles. The regression coefficient estimates are in the positive direction, with a significance value exceeding the critical threshold of 0.05, indicating a unidirectional relationship between the variables. The model determination estimate, at around 57.5%, confirms that TikTok and FOMO are able to explain a significant portion of the variation in students' lifestyles, while the remainder is influenced by factors outside the scope of this study. This finding confirms that TikTok functions not only as a medium of entertainment but also as an agent shaping lifestyles influenced by social and psychological pressures. Therefore, strengthening digital literacy is crucial so that students can use social media more rationally and responsibly.

Micro, small, and medium enterprises (MSMEs) constitute a pivotal pillar of local economic resilience in Bandar Lampung, particularly in the fashion, salon and beauty, and professional service sectors. Notwithstanding their considerable growth potential, many MSMEs continue to encounter structural constraints that impede business expansion, most notably limited entrepreneurial capability, restricted access to capital, and the suboptimal utilization of digital marketing. Against this backdrop, the present study aims to examine the partial and simultaneous effects of entrepreneurship training, capital access, and digital marketing strategy on MSME business expansion. This research employed a quantitative explanatory design with a cross-sectional approach. Data were collected from 100 MSME owners selected through purposive sampling from a population of 2,785 enterprises, and were analyzed using multiple linear regression with SPSS. The findings reveal that entrepreneurship training does not exert a statistically significant effect on business expansion (B = 0.000; p = 0.998), indicating that training, in isolation, has not yet been effectively translated into concrete growth-oriented business practices. By contrast, access to capital has a positive and significant effect (B = 0.263; p = 0.001), demonstrating that financial accessibility enhances operational scale and market development. More importantly, digital marketing strategy emerges as the most influential determinant of business expansion (B = 0.593; p < 0.001), confirming that digital platform utilization substantially strengthens market reach, customer engagement, and business competitiveness. Simultaneously, the three variables significantly affect MSME expansion (F = 34.061; p < 0.001), with an explanatory power of 51.6%. It can therefore be concluded that MSME expansion is primarily driven by the synergy of financial accessibility and digital market adaptation, while entrepreneurship training becomes meaningful only when effectively operationalized within business practice.

Software Defect Prediction (SDP) aims to identify defective modules early in the software development lifecycle to improve software quality and reduce maintenance costs. However, SDP datasets commonly suffer from high dimensionality, feature redundancy, and class imbalance, which can degrade model performance and stability. This study proposes a hybrid feature selection framework to address these challenges and enhance prediction performance. The proposed approach integrates Combined Correlation and Mutual Information (CONMI), which combines the Pearson Correlation Coefficient (PCC) and Mutual Information (MI) to capture both linear and nonlinear feature relevance. The selected features are further refined through Top-K selection, correlation-based filtering to reduce multicollinearity, and Backward Elimination (BE) to obtain an optimal feature subset. To address class imbalance, SMOTE-Tomek is applied by combining over-sampling and data cleaning techniques. Experiments are conducted on twelve NASA MDP datasets using Logistic Regression (LR) and Naïve Bayes (NB) classifiers. The results show that the proposed framework consistently achieves the best performance, with Logistic Regression combined with SMOTE-Tomek obtaining the highest average AUC of 0.7923 ± 0.0714, while NB achieves 0.7554 ± 0.0580. Statistical analysis using a paired t-test indicates that the proposed method significantly outperforms MI+SMOTE-Tomek and BE+SMOTE-Tomek for Logistic Regression, whereas no significant differences are observed for NB. In addition to improving overall classification performance (AUC), the proposed approach also enhances minority class detection, as reflected in improved Recall and F1-score. Overall, the proposed hybrid framework provides an effective and reliable solution for software defect prediction, particularly for high-dimensional and imbalanced datasets.

Slope stability studies are crucial in determining the sustainability and operational safety of mining activities. This research was conducted to analyze the correlation between rock porosity and Unconfined Compressive Strength (UCS) results, as well as the corrleations between Point Load Index (PLI) and Unconfoned Compressive Strength (UCS) results. These two correlations form the primary components of the study. Three types of rock were tested claystone, coal, and siltstone. The results of the study are as follows for the correlation between porosity and Unconfoned Compressive Strength (UCS), claystone yielded a coefficient of determination (R2) of 0.32 is classified as weak correlation, with the linear regression equation Y=-0.11X+6.98. Coal yielded an (R2) of 0.56 is classified a moderate correlation, with the equation Y=-1.98X+103.77. Siltstone yielded an (R2) of 0.86 is classified a strong correlation, with the equation Y=-0.38X+20.02. Regarding the correlation between Point Load Index (PLI) and Unconfoned Compressive Strength (UCS), claystone achieved an (R2) of 0.12 is classified a very weak correlation, with the linear regression equation Y=8.91X. Coal achieved an (R2) of -0.27 is classified a very weak correlation, with the equation Y=27.87X. Lastly, siltstone achieved an (R2) of -0.45 is classified a very weak correlation, with the linear regression equation Y=24,90X.

This study aims to analyze the effect of e-government implementation, Transparency and Maturity of Internal Control System (SPI) on the Quality of Buleleng Regency Government Financial Reports. The research method uses a quantitative approach with a survey method through the distribution of questionnaires to 74 respondents consisting of heads of financial sub-sections and financial report preparation staff at 37 Regional Work Units (SKPD) in Buleleng Regency. The sampling technique uses purposive sampling. Data are analyzed using multiple regression with the help of SPSS 26. The results of the study indicate that the e-government variable does not have a significant effect on the quality of Buleleng Regency government financial reports. Meanwhile, the Transparency and Maturity of Internal Control System (SPI) variables have a positive and significant effect on the quality of Buleleng Regency government financial reports. This finding indicates that the higher the level of implementation of transparency and maturity of the internal control system (SPI), the better the quality of local government financial reports. However, the implementation of e-government has not yet made a significant contribution, possibly due to the suboptimal implementation of the reporting system, which focuses solely on service and administration, and the limited use of technology by human resources. Therefore, the Buleleng Regency government is expected to improve the effectiveness of its e-government implementation and continue to strengthen the transparency and maturity of its internal control system (SPI) to improve the quality of its financial reports. Keywords: E-Government, Transparency, Internal Control System Maturity, financial report quality

The dimensions of healthcare service quality are a concept for measuring service quality. This study aims to determine the effect of the dimensions of healthcare service quality on the satisfaction of inpatients at Cut Nyak Dhien General Hospital in Langsa City. This study uses a quantitative design of the Survey Analytic type with a cross-sectional approach. The population consisted of 121 inpatients with a sample size of 55 respondents using purposive sampling technique. Analysis used multiple logistic regression test (α=0.05). The research results show that there is an influence between Responsiveness p<0.042 with an EXP (B) value of 11.361, Assurance p<0.008 with an EXP (B) value of 20.163, Empathy p<0.018 with an EXP (B) value of 13.547, Reliability p<0.033 with an EXP (B) value of 6.896 on inpatient patient satisfaction (p<0.05), while the Tangible variable shows no influence with p<0.088 and an EXP (B) value of 4.967. Among these variables, the one that significantly affects inpatient patient satisfaction is the Assurance variable with p<0.008 and an EXP (B) value of 20.163. It is recommended to continuously improve the quality of service comprehensively in every dimension of service quality, strengthen the competence and professionalism of healthcare personnel, enhance the speed and accuracy of service, and build good communication to improve the quality of inpatient services and maintain patient trust in the hospital.  

This study aims to analyze the influence of digital marketing through Instagram on purchasing decisions at UMKM Jamu Bu Bekti in Karawang Regency. The research uses a quantitative approach, with data collected through questionnaires distributed to consumers who have seen or purchased the products. The data analysis technique applied is regression analysis to examine the relationship between marketing content and promotional variables on consumer purchasing decisions.The results show that marketing content shared on Instagram does not have a significant effect on purchasing decisions. However, the content is considered quite attractive, informative, and helpful in providing product information to consumers. On the other hand, promotion has a positive and significant impact on increasing consumer interest and encouraging purchasing decisions. This indicates that consumers are more responsive to promotional strategies such as discounts, bonuses, or special offers rather than relying solely on content quality.These findings suggest that promotional strategies play a crucial role in digital marketing, especially for small and medium enterprises (SMEs). Therefore, business owners are advised to focus more on creating attractive, creative, and targeted promotional activities on social media to boost sales. This study is expected to contribute to the development of more effective, efficient, and sustainable digital marketing strategies for SMEs in the future.

This study aims to analyze the effect of financial literacy and lifestyle on financial management of students of the Management Study Program at Universitas Pamulang. This research uses a quantitative method with an associative approach, with data collected through questionnaires distributed to 160 respondents. Data analysis was conducted using validity tests, reliability tests, classical assumption tests, simple and multiple linear regression analysis, t-test, F-test, and coefficient of determination (R²). The results show that partially financial literacy has a positive and significant effect on financial management with a t-value of 7,161 > t-table 1.975 and a significance value of 0.000 < 0.05, while lifestyle also has a positive and significant effect with a t-value of 6,881 > t-table 1.975 and a significance value of 0.000 < 0.05. Simultaneously, financial literacy and lifestyle have a significant effect on financial management with an F-value of 853.671 > F-table 3.05 and a significance value of 0.000 < 0.05. The coefficient of determination of 0.916 indicates that 91,6% of the variation in students’ financial management is explained by financial literacy and lifestyle, while the remaining 8,4% is influenced by other factors outside this study.

This study aims to analyze the influence of Psychological Capital, work motivation, and workload on the performance of Training Officers at the Infantry Education Center (Pusdikif) of the Indonesian Army's Infantry Training Center (Pussenif. This study uses a quantitative approach with an explanatory survey design. The research population consists of all 60 non-commissioned officer trainers at Pusdikif Pussenif TNI AD. Data collection was conducted using a five-point Likert scale questionnaire. Data analysis was performed using multiple linear regression with the help of SPSS 29. The results show that Psychological Capital has no significant effect on the performance of non-commissioned officer trainers. Work motivation has a positive and significant effect on performance and is the most dominant variable. Workload has a positive and significant effect on performance. Simultaneously, Psychological Capital, work motivation, and workload have a significant effect on the performance of Training Officers. The research model has a very strong relationship (R = 0.856) with an explanatory power of 73.3%. This study shows that the performance of military trainers is more influenced by work motivation and task demands than by personal psychological factors. The results of this study are expected to serve as a basis for the leadership of the Indonesian Army's education units in increasing work motivation and managing the workload of trainers proportionally to support the improvement of military education performance.

Public companies must maintain sustainability, as it is related to their value. A company's value can be measured by its share price; a higher market price indicates a company's financial performance and investment returns for investors. A phenomenon has been observed in the consumer non-cyclical sector, which experienced declines and fluctuations in value from 2020 to 2024. This phenomenon indicates that falling share prices lead to a decline in company value. This study aims to analyze the influence of Corporate Social Responsibility, Tax Avoidance, and Dividend Policy on Company Value in companies in the Consumer Non-Cyclical sector listed on the Indonesia Stock Exchange during the 2020-2024 period. The study sample consisted of 10 companies with 50 data observations selected using a purposive sampling technique. Data analysis was conducted using panel data regression with the help of EViews 12 software. The results of the study indicate that (1) Corporate Social Responsibility, Tax Avoidance, and Dividend Policy as a whole have an effect on Company Value, (2) Corporate Social Responsibility partially has no effect on Company Value, (3) Tax Avoidance partially has no effect on Company Value, (4) Dividend Policy partially has no effect on Company Value. These findings prove that Corporate Social Responsibility, Tax Avoidance, and Dividend Policy together are able to influence company value, even though each variable does not have an effect on company value.

This study aims to analyze and obtain empirical evidence regarding the effect of profitability, leverage, and sales growth on tax avoidance in energy sector companies listed on the Indonesia Stock Exchange (IDX) for the 2020–2024 period. This research method uses a quantitative approach with secondary data in the form of annual financial reports obtained from the official IDX website and related company websites. The sampling technique used a purposive sampling method to obtain a sample of companies that met the research criteria during the observation period. The dependent variable in this study is tax avoidance, which is proxied by the Effective Tax Rate (ETR), while the independent variables consist of profitability as measured by Return on Assets (ROA), leverage as measured by the Debt to Equity Ratio (DER), and sales growth as measured by annual sales growth. The data analysis technique uses panel data regression through the stages of selecting the best model, classical assumption testing, multiple linear regression analysis, and hypothesis testing. The results of the study indicate that profitability, leverage, and sales growth simultaneously influence tax avoidance. Partially, profitability influences tax avoidance, while leverage and sales growth do not.

This Study aims to analyze the effect of digital literacy and competence on employee productivity at PT PLN (Persero) Customer Service Unit (ULP) Takalar. This study employs a quantitative approach using a survey method. The population consists of all employees of PT PLN (Persero) ULP Takalar, and a census sampling technique was applied, meaning all members of the population were selected as respondents. Data were collected through questionnaires and analyzed using multiple linear regression with the assistance of SPSS software. The results indicate that digital literacy has a positive and significant effect on employee productivity. This means that the better the employees’ ability to understand and utilize digital technology, the higher their level of productivity. In contrast, employee competence was found to have a negative and significant effect on productivity. This finding suggests that increasing competence does not automatically lead to higher productivity if it is not supported by other relevant factors. These findings imply that improving competence without proper job placement, effective task management, and optimal utilization of skills may actually reduce employee productivity. Therefore, it is recommended that PT PLN (Persero) ULP Takalar not only enhance employees’ digital literacy and competence but also ensure alignment between competencies and job requirements through more effective human resource management in order to improve overall productivity

Dividend payment is an important financial decision that reflects a company’s performance and prospects from the perspective of investors. However, companies included in the LQ45 index still experience fluctuations in dividend payment policies from year to year. This study aims to analyze the effect of leverage, firm size, profitability, and liquidity on dividend payments of companies listed in the LQ45 index on the Indonesia Stock Exchange (IDX) during the 2023–2024 period. This research employs a quantitative approach using secondary data obtained from published financial statements. The sample was selected using a purposive sampling method, resulting in 33 companies with a total of 60 observations. Data analysis was conducted using panel data regression with the assistance of SPSS software. Leverage is measured by the Debt to Asset Ratio (DAR), firm size by the natural logarithm of total assets (LnTA), profitability by Return on Assets (ROA), liquidity by the Current Ratio (CR), and dividend payment by the Dividend Payout Ratio (DPR). The results show that leverage, firm size, profitability, and liquidity simultaneously have a significant effect on dividend payments. Partially, firm size and profitability have a positive and significant effect on dividend payments, while leverage and liquidity do not have a significant effect. These findings indicate that companies with larger firm size and higher profitability tend to have a greater ability to distribute dividends to investors.

This study aims to examine the extent to which taxpayers’ attitudes toward e-filing influence tax compliance, with the implementation of e-filing positioned as a mediating variable among employees of PT Selalu Cinta Indonesia (SCI) registered at the Primary Tax Office (KPP Pratama) of Salatiga City. The population comprised 18,244 employees, from which a sample of 100 respondents was selected using purposive sampling. Data were processed and analyzed using simple linear regression and path analysis. The results indicate that attitudes toward e-filing have a significant effect on taxpayer compliance (t = 7.708; sig. < 0.001) and also significantly influence the level of e-filing implementation (t = 7.644; sig. < 0.001). Furthermore, the implementation of e-filing has a significant impact on taxpayer compliance (t = 150.765; sig. < 0.001). Additional findings reveal that e-filing implementation acts as a partial mediator in the relationship between attitudes toward e-filing and taxpayer compliance, with a total effect value of 1.225. Overall, these findings reinforce the Theory of Planned Behavior framework, which posits that positive attitudes toward a system can foster the formation of specific behaviors, particularly in the context of tax compliance.

The rapid growth of beverage franchises in Indonesia, particularly MIXUE with over 4,000 outlets, necessitates an in-depth examination of the financial management strategies underlying its success. This study aims to analyze the effects of working capital management, supply chain support, and operational cost efficiency on financial performance, as well as to evaluate the investment feasibility of the MIXUE franchise in Indonesia. A mixed-methods sequential explanatory approach was employed, utilizing multiple regression analysis and capital budgeting methods including Net Present Value (NPV), Internal Rate of Return (IRR), Payback Period (PP), and Return on Investment (ROI). Data were collected from 50 franchise outlets across Jakarta, Bandung, Surabaya, and Semarang during 2022-2024, supplemented by in-depth interviews with 15 franchisees and 3 regional managers. Results reveal that all three independent variables significantly and positively affect financial performance: working capital management (β = 0.412; p = 0.002), supply chain support (β = 0.358; p = 0.008), and operational cost efficiency (β = 0.486; p < 0.001) with R² = 0.684. Investment feasibility analysis indicates an average positive NPV of IDR 290.1 million, IRR 36.5%, PP 22.2 months, and ROI 56.5%. This study contributes novel insights by integrating financial and supply chain analysis within the context of beverage franchising in emerging Asian markets, providing a comprehensive evaluation framework for prospective investors and franchise system developers.

Multicollinearity is one of the common issues in multiple linear regression that can lead to instability in the estimation of regression coefficients. This study aims to examine the impact of multicollinearity on regression models and to evaluate the use of Ridge Regression as an alternative estimation method. The study employs simulated data consisting of 1,000 observations, including one dependent variable and four independent variables designed to exhibit high correlation. The analysis begins with model estimation using the Ordinary Least Squares (OLS) method, followed by multicollinearity testing using the Variance Inflation Factor (VIF). The OLS results indicate that most independent variables significantly influence the dependent variable, with a coefficient of determination (R²) of 0.9863. However, the high VIF values reveal the presence of strong multicollinearity in the model. To address this issue, Ridge Regression is applied, with the optimal penalty parameter determined through cross-validation, yielding a lambda value of 4.201589. The results show that the regression coefficients in the Ridge model undergo shrinkage, resulting in greater stability compared to the OLS estimates. Model evaluation indicates that the Mean Squared Error (MSE) for the OLS model is 24.77, whereas the Ridge model produces an MSE of 29.72. Although the Ridge model exhibits a slightly higher MSE, it effectively mitigates the impact of multicollinearity and provides more stable parameter estimates.

The development of digital technology has encouraged businesses to utilize social media as an effective marketing tool, particularly in the fashion industry targeting Generation Z. In addition to digital promotional strategies, product quality is also an important factor influencing consumers’ purchase decisions. This study aims to analyze the effect of social media marketing and product quality on purchase decisions among consumers of Jims Honey Kaliwungu Branch. This research employed an explanatory type with a quantitative approach. The sample consisted of 100 respondents selected using purposive sampling. Data were collected through questionnaires and analyzed using validity testing, reliability testing, multiple linear regression, t-test, F-test, and the coefficient of determination with the assistance of SPSS. The results show that social media marketing has a positive and significant effect on purchase decisions, with a t-value of 2.293 greater than the t-table value of 1.984 and a significance value below 0.05. Product quality also has a positive and significant effect on purchase decisions, with a t-value of 6.631 greater than the t-table value of 1.984 and a significance value below 0.05. Simultaneously, social media marketing and product quality have a significant effect on purchase decisions, with an F-value of 25.994 greater than the F-table value of 3.09 and a significance value below 0.05. The coefficient of determination of 0.349 indicates that both independent variables contribute 34.9% to purchase decisions. These findings confirm that product quality has a more dominant influence than social media marketing in encouraging purchase decisions among consumers of Jims Honey Kaliwungu Branch.

The retention of customers in the retail banking sector is a critical economic imperative; however, predictive modeling is frequently hindered by severe class imbalance and the “Black Box” nature of complex algorithms. This study proposes a Heterogeneous Stacking Ensemble framework integrating XGBoost, CatBoost, and Random Forest base learners with a Logistic Regression meta-learner to forecast customer attrition. To overcome the pervasive “Majority Class Bias,” we introduce a “Dual-Imbalance Defense” that synergizes the Synthetic Minority Over-sampling Technique (SMOTE) with algorithmic cost-sensitive penalization. Furthermore, moving beyond standard accuracy metrics, the framework mathematically derives a dynamic classification threshold to guarantee a strict 0.90 recall rate, actively optimizing the capture of at-risk capital. Model opacity is addressed through the integration of a SHapley Additive exPlanations (SHAP) TreeExplainer. This cooperative game theory approach provides localized, patient-level “Reason Codes” for regulatory compliance and reveals global systemic vulnerabilities, including non-linear drivers such as the “Product Paradox.” Achieving a 0.90 recall rate and an AUC of 0.8654, this framework provides a statistically robust and operationally transparent tool for targeted customer retention.

Vaname shrimp (Litopenaeus Vannamei) is one of Indonesia's fishery commodities with high economic value. Vaname shrimp production in Indonesia continues to increase. However, obstacles sometimes arise in cultivation activities, such as the emergence of shrimp diseases and poor water quality. High stocking density and shrimp feeding can cause a decline in water quality. In addition, pond water quality is influenced by pond location and the surrounding environment, such as agriculture, settlements, mangroves, and the sea. This causes ponds to have different water qualities. One of the diseases that often attacks shrimp farming is caused by the bacterium Vibrio sp. The abundance of Vibrio sp. bacteria is closely related to pond water quality and the environmental conditions around the pond. The methods used were TPC testing and multiple linear regression testing. Based on the results of the study, the abundance of Vibrio sp. bacteria in pond A was the highest at 8.3 x 102, and pond C had the lowest at 3.1 x 102. Water quality testing in three different ponds showed safe limits for cultivation, except for nitrite testing. Based on the simple linear regression test, the water quality parameters that significantly affect the abundance of Vibrio sp. bacteria are pH, temperature, and nitrite.