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This study try to examine the impact of institutional, managerial, and public kepemilikan structures on the level of environmental, social, and governance (ESG) practices in manufacturing companies listed on the IDX between 2020 and 2024. This study's findings are supported by increasing transparency and business continuity, also in guiding ESG practices. The research method that is used is quantitative analysis using panel regression analysis. The study's sample consists of 27 manufacturing companies selected using the purposive sampling method, yielding a total of 135 observations over of a few years. The analysis's findings indicate that all the ownership do not significantly affect ESG. Conversely, company size and employee productivity as control variables have a positive impact on the ESG threshold. This shows the structure of kepemilikan is not the most important factor in determining ESG transparency for Indonesian manufacturing companies, which are primarily focused on the importance of jangka pendek. Implicitasi penelitian ini mengindikasi bahwa pengungkapan ESG is more negatively impacted by internal company capacity than by stock composition, therefore external regulations and technical assistance are crucial factors in guiding business operations.

This study aims to analyze the effect of price and product quality on purchasing decisions of Gudang Garam Signature Kretek cigarettes in the premium machine-made kretek segment. The Indonesian tobacco industry continues to face sustained regulatory pressure through excise tax increases and intensifying brand competition, prompting consumers to reassess purchasing decisions using both rational evaluation and experiential judgment. A quantitative correlational approach was employed in this study. Primary data were collected through structured Likert-scale questionnaires distributed to 100 active consumers of Gudang Garam Signature Kretek selected using purposive sampling techniques. Data analysis was conducted through validity testing, reliability testing, and multiple linear regression analysis using SPSS software. The results indicate that price and product quality have a positive and significant influence on purchasing decisions, both partially and simultaneously. Product quality emerged as the most dominant factor, suggesting that premium cigarette consumers prioritize consistent quality, taste, aroma, and overall consumption experience as the primary basis for decision-making. Meanwhile, price remains an important rational reference for assessing the fairness between perceived benefits and financial sacrifice. Simultaneously, both variables explain 50 percent of the variation in purchasing decisions, while the remaining variance is influenced by other factors outside the research model. These findings highlight that purchasing decisions in the premium cigarette market are shaped by a value-based assessment, where sustained product quality and adaptive pricing strategies play a critical role in maintaining consumer loyalty amid regulatory pressure and evolving market dynamics

The agricultural sector is a vital pillar in maintaining food security and enhancing the livelihoods of rural communities. In an effort to improve agricultural productivity, the Government of Lamongan Regency, through the Food Security and Agriculture Agency (DKPP), has implemented the Agricultural Facilities and Infrastructure Provision and Development Program. This program is designed to strengthen agricultural production capacity by supporting the availability of farming machinery, improving irrigation networks, and developing farm access roads. Despite its strategic importance, the program’s implementation continues to encounter various obstacles, including constrained budget availability, unequal distribution of agricultural facilities, reliance on rain-fed irrigation systems, substandard farm road infrastructure, and limited intensity of agricultural extension services. This research aims to examine the implementation of the Agricultural Facilities and Infrastructure Provision and Development Program in Sukodadi Village, Sukodadi District, Lamongan Regency. The study adopts a qualitative descriptive approach, utilizing data collected through in-depth interviews, direct field observations, and document review. Analysis is conducted using the Van Meter and Van Horn policy implementation framework, which emphasizes six key variables: policy standards and objectives, resource adequacy, characteristics of implementing organizations, inter-organizational communication, implementer disposition, and social, economic, and political conditions. The results reveal that although policy standards and objectives are well defined, program execution remains suboptimal due to limited resources and insufficient institutional support at the operational level. Consequently, stronger coordination among implementing actors and improved resource optimization are necessary to achieve more effective and sustainable agricultural development outcomes.  

The third trimester of pregnancy is a challenging period since pregnant women experience various physical and psychological changes that can affect their readiness for childbirth. High anxiety levels and the presence of pregnancy complications are known to reduce maternal preparedness for labor. This study aims to determine the relationship between anxiety levels and pregnancy complications with the readiness of third trimester pregnant women in facing childbirth in the working area of Benteng Community Health Center, Selayar Islands Regency. This research used a quantitative approach with a correlational design and a cross-sectional method. The population consisted of all third trimester pregnant women, with a total sample of 86 respondents selected using purposive sampling. The research instruments included an anxiety questionnaire using the Hamilton Anxiety Rating Scale (HARS), a pregnancy complication checklist, and a childbirth readiness questionnaire. Data were analyzed using the Chi-Square test and multiple logistic regression at a significance level of α = 0.05. The results of the study showed no significant relationship between anxiety and readiness for childbirth (p < 0.550) or between pregnancy complications and readiness for childbirth (p < 0.690). Therefore, it can be concluded that anxiety and pregnancy complications are not significantly related to the readiness of pregnant women in the third trimester for childbirth. This indicates that maternal readiness is influenced by factors other than the variables studied, such as knowledge, family support, and previous childbirth experiences.

This study investigates the influence of Apparatus Competency and Information Systems on Community Political Participation in the Local Government Head Election during the COVID-19 pandemic era in Karawang Regency. The COVID-19 pandemic has posed significant challenges to democratic processes, particularly in maintaining voter participation while ensuring public health safety. Employing a mixed-methods approach combining quantitative and qualitative data with Structural Equation Modeling (SEM) analysis, this research analyzed data from 263 respondents across various election administrative units. The results indicate that: (1) Apparatus Competency does not have a significant positive effect on Community Political Participation (T-value = 1.01 < 1.96); (2) Information Systems have a significant positive effect on Community Political Participation (T-value = 2.78 > 1.96; path coefficient = 0.67). The combined contribution of both variables explains 76% of the variance in political participation. From these findings, the study proposes the Skills Democracy Model, emphasizing that digital information skills and organizational experience are critical determinants of democratic participation quality during pandemic conditions. These findings have significant implications for election governance reform and e-democracy development in Indonesia.

The competitiveness of gig workers in the digital economy era raises issues such as competency gaps with market needs and instability in the quality of gig workers' work. This study explains the influence of training, work skills, and independent learning on the performance of gig workers who participate in training programs at the Central Java Province Cooperative and SME Training Center. Therefore, this study aims to examine the influence of each variable partially and simultaneously. This study uses a quantitative approach by distributing questionnaires to the entire population or using a saturated sample of 50 gig workers participating in training at BALATKOP UKM. The data was obtained using a Likert scale questionnaire instrument compiled based on the operational definitions of the variables and analyzed using multiple linear regression analysis to test the influence of training (X2), work skills (X2), and independence (X3) on performance (Y). The results of the study show that training, job skills, and independent learning each have a positive and significant effect on gig worker performance, and simultaneously, these three variables have a 66.5% effect on performance. This synthesis of findings confirms that gig worker performance is not only determined by the quality of training programs and technical skill mastery, but also by the ability to manage the learning process independently. Therefore, the conclusion is that the development of training programs at BALATKOP UKM needs to be designed in an integrated manner to simultaneously strengthen training, work skills, and independent learning as a strategy for improving the sustainable performance of gig workers.

This study aims to analyze the influence of financial literacy, e-money use, and lifestyle on the financial behavior of accounting students in the context of a cashless society. The research population includes students of the accounting study program of the Faculty of Economics and Business, University of Muhammadiyah Gresik, Semen Indonesia International University, and Gresik University. The sampling technique used accidental sampling with a total of 120 respondents in the 6th semester. Primary data was obtained through the distribution of questionnaires, then analyzed using quantitative methods with the help of SmartPLS software. The results of the study show that financial literacy does not have a significant effect on students' financial behavior. Conversely, the e-money variable has a significant positive influence on financial behavior, indicating that the use of digital transactions encourages more practical financial management patterns. In addition, lifestyle has also been shown to have a significant positive effect on financial behavior, indicating that students' consumption preferences and lifestyle also determine how they manage their finances in the cashless era. This research makes an empirical contribution in understanding the factors that influence the financial behavior of the younger generation, as well as being the basis for the development of financial literacy and policies related to digital payment systems in the higher education environment.

This study aims to analyze the effect of the implementation of e-Samsat and progressive tax on motor vehicle taxpayer compliance at the Bandung City Samsat Office III Soekarno-Hatta. The background of this study is based on the fact that the level of taxpayer compliance has not yet reached an optimal level, despite the government’s efforts to implement technology-based tax services and fair taxation policies. This research employs a quantitative approach, with data collected through questionnaires distributed to motor vehicle taxpayers. The collected data were analyzed using statistical methods to examine both partial and simultaneous effects of the variables.The results indicate that the implementation of e-Samsat has a positive and significant effect on motor vehicle taxpayer compliance. The convenience, speed, and efficiency provided by the e-Samsat system enhance taxpayers’ awareness and discipline in fulfilling their tax obligations. Furthermore, progressive tax is also proven to have a positive effect on taxpayer compliance. The application of higher tax rates based on the number of vehicles owned encourages a sense of responsibility and fairness among taxpayers. Simultaneously, the implementation of e-Samsat and progressive tax positively influences motor vehicle taxpayer compliance and contributes to the optimization of regional tax revenue. Therefore, continuous improvement of the e-Samsat system, along with the fair and transparent implementation of progressive tax policies, is essential to sustainably increase taxpayer compliance and support local revenue growth.

This study aims to analyze the influence of influencers and electronic word of mouth  (e-WOM) on the purchase decision of Bika Ambon Ahun in Medan City. The rapid development of social media has transformed how consumers obtain information and make purchasing decisions, making influencers and e-WOM essential components in shaping consumer perceptions and behavior. This research employs an associative quantitative method with data collected through questionnaires distributed to consumers who were familiar with the product through social media. The data were analyzed using partial (t-test) and simultaneous (F-test) analyses to examine the strength of the relationship between the independent variables and the purchase decision. The findings indicate that influencers have a positive and significant effect on purchase decisions, as consumers perceive influencer review content to be credible, engaging, and persuasive. Likewise, e-WOM demonstrates a positive and significant influence, supported by consumer trust in online reviews, comments, and recommendations that serve as strong social proof before making a purchase. Simultaneously, both influencers and e-WOM contribute 68.4% to the variation in purchase decisions, while the remaining 31.6% is influenced by other external factors. These results emphasize that the combined influence of influencers and e-WOM generates a synergistic effect that strengthens consumer interest, trust, and confidence in purchasing local products such as Bika Ambon Ahun. The study implies the importance for businesses to optimize digital marketing strategies by collaborating with credible influencers and encouraging positive online reviews as a means to reinforce consumer purchase decisions.  

College represents a critical transitional period requiring high adaptation, where students often face escalating academic demands triggering psychological pressure. This study aims to deeply analyze the reciprocal relationship between sleep patterns and academic stress levels, and identify their subsequent impacts on cognitive function (concentration) and students' physical health. This study employs a qualitative method with a Systematic Literature Review approach. Data were collected through comprehensive searches of accredited national and reputable international scientific articles published within the last five years (2020–2025). Literature selection was conducted rigorously using specific keywords to screen empirical studies relevant to stress, sleep, and student health variables. Data synthesis reveals a strong and consistent negative correlation. High levels of academic stress whether stemming from the adaptation phase of new students (initiation), thesis preparation workload, or role conflicts in working students are significantly associated with decreased sleep quality. Physiologically, stress triggers increased cortisol levels causing insomnia, shortened sleep duration, and prolonged sleep latency. Subsequent impacts are proven to drastically reduce learning concentration and trigger physical health disorders, including an increased risk of primary dysmenorrhea in female students. This study concludes that academic stress and sleep disturbances form a destructive cycle that exacerbates one another. Therefore, holistic institutional interventions in the form of sleep hygiene education and stress management training are needed to break this chain for the sake of student well-being and academic performance.

The rapid expansion of the construction sector in Maumere has significantly escalated the demand for essential building materials, particularly concrete blocks. This surge has intensified market competition among local manufacturers. For a producer such as PT Rajawali Sakti, ensuring the quality of its construction materials and leveraging Word-of-Mouth (WOM) are critical strategies to influence consumer procurement decisions. This study aims to analyze the influence of product quality and WOM on the purchasing decisions of consumers of PT Rajawali Sakti’s concrete blocks in Maumere. Employing a quantitative method with a descriptive associative approach, this research collected data from 100 respondents via a Likert-scale questionnaire. The data were analyzed using multiple linear regression to determine the statistical relationships between the variables. The results indicate that product quality has a positive and significant effect on purchasing decisions. The model’s R-squared value of  reveals that the combined contribution of product quality and WOM to purchasing decisions is while the remaining is influenced by external factors beyond the scope of this study. These findings provide critical managerial insights for PT Rajawali Sakti and similar construction material manufacturers, serving as an empirical basis for strategic evaluations aimed at enhancing material quality and optimizing WOM communication to improve market competitiveness and consumer adoption.

Type 2 diabetes is a persistent medical condition with an increasing incidence that requires long-term treatment. One of the decisive factors in blood glucose control Patient self-awareness is a key variable examined in this study. The research was conducted to assess the relationship between self-awareness and blood glucose levels among individuals with type 2 diabetes in the Tuban Community Health Center area. A correlational analytic study with a cross-sectional design was utilized. The study involved a population of 135 patients, with a sample of 101 respondents selected using simple random sampling.Research data collection was conducted using a self-awareness questionnaire and a blood glucose observation sheet. Data analysis was performed using a chi-square test with a significance level of 0.05. The results of the analysis showed a p-value of 0.002 (p < 0.05), indicating a significant association between self-awareness and blood glucose levels. Based on these results, the study findings generally indicate that greater self-awareness typically allows for more optimal control of blood glucose levels.  

Forgiveness can be described as a response given by someone who has experienced hurt in order to avoid revenge and expressions of anger towards the perpetrator, while choosing to show compassion, affection, love, and positive behavior. One of the factors that influence forgiveness is emotional intelligence, which includes an individual's ability to motivate themselves, show resilience to failure, control emotions, maintain satisfaction, and regulate psychological conditions. The purpose of this study was to determine whether there is a relationship between emotional intelligence and the level of forgiveness among high school students in Montong District. This research is non experimental with a correlational analytical design using a cross sectional approach. The research population included 592 high school students in Montong District. The sampling technique applied was probability sampling with cluster random sampling, resulting in a sample of 239 students. Data collection was conducted using questionnaires that measured emotional intelligence and forgiveness. The results of the analysis using the Spearman test at α = 0.05 showed p = 0.000 < 0.05 with a correlation coefficient of r = 0.389, indicating a low relationship between the two variables, thus accepting the hypothesis. Based on this description, it can be concluded that there is a relationship between emotional intelligence and the level of forgiveness among high school students in Montong District.

Thіs studу aіmеd to examіnе the eligibilitу оf tеасhеr honorаrium bу іmрlemеntіng a classifiсatіon method usіng thе Decіsіon Тree algorithm. Тhе primary іssuе addressеd in thіs rеsеаrсh is the absеnce of а fair and dаtа-driven salarу sуstеm аt SМA YPKPР. А сlаssificatіon aрproach was emрloуеd to сatеgorіze teасhers intо "Elіgіble" and "Not Elіgiblе" grоuрs basеd оn attributеs such аs tеachіng hоurs, hourly wаge, eduсatiоn lеvel, jоb роsіtіon, сеrtіfіcаtіоn allowаnсe, аnd schoоl status.Thе сlаssifiсatіon model was dеveloрed usіng RаріdМiner sоftwаrе. Тhе datasеt was dіvidеd into trainіng and tеsting sets usіng a sрlіt datа technique. Тhe modеl wаs еvaluatеd usіng metrісs such as acсuraсy, рrecisіоn, rеcall, and сonfusiоn matrіх. The rеsults indіcаtеd that thе Dесіsiоn Тree model аchіеved аn асcurасy оf 93.75% in сlаssіfуing tеаchеr honorarium еligіbіlity. Тeасhing hours and hourlу wаge werе idеntifіеd as thе twо most іnfluеntial variables іn the сlаssіfісаtіоn рroсеss.Аs a form of vаlіdatіоn, addіtionаl statistіcal аnalysis was соnducted usіng SРSS. The Рeаrsоn cоrrelаtіon tеst showеd а sіgnіficаnt relаtionshір bеtween teaching hours and hourlу wаge wіth thе tоtаl honоrаrіum rеcеivеd. Мultіplе .Lineаr rеgressiоn аnalysis resulted іn аn R Squаre valuе of 0.860, indicаting that 86% оf thе varіation in hоnorarium сan be eхрlаіnеd bу thе twо vаrіаblеs.Тhis study іs expесtеd tо serve аs а foundаtіоn for mоre objеctive аnd dаtа-drіven dеcisіоn-mаking іn thе tеaсhеr comреnsation sуstem. Тhe findіngs dеmоnstrаte thаt а combinаtiоn of datа minіng аnd stаtіstісаl аnаlуsis aрprоаches сan bе usеd to devеlop a trаnsparent, fair, аnd efficient sаlаrу system.

The utilization of digital technology in government administration is a critical measure to improve employee performance and the efficiency of public services. However, the effectiveness of implementing this technology is highly determined by the degree to which employees accept the digital systems being used. This study aims to analyze the impact of digital technology acceptance on employee performance at the Mojoroto District Office in Kediri City. The research employs a quantitative method with an explanatory design. Information was obtained through a questionnaire survey distributed to all employees at the Mojoroto District Office, totaling 30 respondents, using total sampling techniques. Indicators of digital technology adoption were evaluated based on perceptions of benefits, operational ease, social pressure, and infrastructural support, while employee performance was assessed according to the quality of work output and responsibilities. Data analysis involved descriptive statistics, validity and reliability tests, and ordinal linear regression. The study findings indicate that digital technology acceptance has a positive and significant influence on employee performance. The coefficient of determination figure reveals that digital technology adoption can explain a large part of the fluctuations in employee performance, with the remaining variation influenced by variables outside the research model. These results imply that the greater the level of digital technology acceptance, the better the resulting employee performance. This study concludes that strengthening digital capabilities, technical guidance, and institutional support are key strategies for enhancing employee performance and public service quality at the district level.

There is one problem related with source Power man that is turnover that occurred at Hospital X and is known reach more from 10%. Research aiming for analyze Job Satisfaction as an intervention in connection between compensation compensation, leadership transformational, and burden Work to turnover intention in nurses power Work contract at Hospital X. Research use approach quantitative with type explanatory. Population in study is all over Labor Nurse Contract at Hospital as many as 562 people. The sampling method used is non-probability sampling. Research data This using primary data that is done with share questionnaire in a way direct through google form with alternative answer use scale Likert. Research This use approach Structural Equation Model (SEM) with measurement model using Smart PLS program version 3.2.9. Research results This find that in a way simultaneous all over variable influential to turnover intention. In partial compensation, leadership transformational, and burden Work found own influence significant to Job Satisfaction. More carry on in a way partial satisfaction too work, compensation, leadership transformational, and burden Work own influence significant to turnover intention.

This study aims to examine the effect of students’ organizational involvement on public speaking skills among students of Universitas Muhammadiyah Jember. Public speaking skills are essential soft skills required by students in both academic and professional settings, particularly for those who actively engage in public and organizational activities. This research employed a quantitative approach with an associative research design. The independent variable in this study was students’ organizational activeness (X), while the dependent variable was public speaking skills (Y). The research sample consisted of 169 students of Universitas Muhammadiyah Jember selected using proportionate stratified random sampling. Data were collected through a closed-ended questionnaire using a Likert scale, which had been tested for validity and reliability. Data analysis was conducted using descriptive and inferential statistical methods. The results showed that the organizational activeness instrument had a high level of reliability, while the public speaking skills instrument demonstrated a moderate level of reliability. Overall, students’ involvement in organizations plays an important role in developing public speaking skills through communication experiences, active participation, and increased self-confidence. This study is expected to serve as a reference for higher education institutions and student organizations in designing programs that support the development of students’ soft skills, particularly public speaking abilities.

Tax Management refers to a company’s efforts to manage its tax obligations efficiently and legally in order to optimize net income. This study aims to examine the effect of Fixed Asset Intensity and Leverage on Tax Management, with Profitability as a moderating variable, in mining companies listed on the Indonesia Stock Exchange (IDX) for the 2021–2024 period. This research is conducted because tax management practices are considered to potentially influence corporate profitability and financial performance. The study is grounded in Agency Theory and employs a quantitative approach. The sample was selected using purposive sampling, resulting in 28 companies observed over four years, with a total of 112 secondary data observations obtained from annual reports or financial statements. Data analysis was performed using EViews 13 with a Moderated Regression Analysis (MRA) approach. The findings indicate that: (1) Fixed Asset Intensity has no significant effect on Tax Management; (2) Leverage has a significant negative effect on Tax Management; (3) Profitability does not moderate the relationship between Fixed Asset Intensity and Tax Management; and (4) Profitability strengthens the effect of Leverage on Tax Management.

Rapid developments in the Artificial Intelligence (AI) industry have triggered an increased need for workers with specialized competencies, which has implications for significant variations in salary levels. This research aims to analyze the factors that influence salaries in the AI sector using the multiple linear regression method. The dataset used includes 15,000 AI job vacancies with variables including job and company characteristics. The data was engineered via the one-hot encoding method and divided into two parts: training data (80%) and test data (20%). The analysis results show that the regression model is able to explain 85% of the variation in salary, with an R² value of 0.85 and a Root Mean Square Error (RMSE) of USD 23,221. The three main factors identified as having a significant influence on salaries in the AI field are work experience, company location, and the industry in which the company operates. The experience factor reflects the skills and knowledge developed over many years, which can increase productivity (Rony et al., 2023). Company location also plays an important role, as the cost of living and demand for skilled labor varies by region (Badran, 2019). Additionally, the specific industry in which an employee works influences salary, given that more developed industries can often offer higher compensation (Huang, 2025). This research makes a significant empirical contribution to the understanding of compensation structures in the AI labor market.

The increasing number of Indonesian Migrant Workers (TKW) working abroad, particularly through programs organized by BP2MI, has become a significant concern in managing the labor export process. One of the challenges faced is the uncertainty of the number of TKW to be sent each year, which is influenced by various external and internal factors. Therefore, this study aims to apply artificial neural networks (ANN) with a backpropagation algorithm approach to predict the number of TKW that will be processed by BP2MI. This method was chosen due to its ability to recognize patterns and nonlinear relationships between variables that affect the decision-making process for TKW export. In this study, the data used includes factors such as the number of job seekers, government policies, and the condition of the international labor market. The artificial neural network with the backpropagation algorithm is used to train the model based on existing historical data, with the goal of generating accurate predictions regarding the number of TKW to be processed in the coming years. The results of the tests show that the developed model can provide fairly accurate predictions and can serve as a tool for BP2MI in planning and managing the export of TKW more effectively. With the application of this technology, it is expected that the decision-making process related to TKW export can become more efficient and well-predicted.