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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

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 investigates the optimization of claims under the Indonesian Case-Based Groups (INA-CBGs) payment mechanism within the National Health Insurance Program (Jaminan Kesehatan Nasional) at Hospital X in Serang. The research aims to analyze the influence of managerial competence, digital adoption, and organizational behavior on claim effectiveness, with policy implementation serving as a moderating variable. Employing a quantitative explanatory approach, data were collected from 144 respondents comprising management staff, casemix teams, and medical record officers through questionnaires and structured interviews. Structural Equation Modeling–Partial Least Square (SEM-PLS) was applied to examine the relationships among variables. Findings reveal that managerial competence, digital adoption, and organizational behavior significantly and positively affect the optimization of INA-CBGs claims. Furthermore, the implementation of the National Health Insurance Program policy strengthens these relationships, enhancing claim efficiency and equity. The results align with the Resource-Based View theory, highlighting the strategic role of internal resources in achieving organizational performance. Managerial implications include capacity building for managers, integration of hospital information systems (SIMRS) with e-Claim platforms, and fostering collaborative organizational culture. Overall, the study underscores the importance of managerial, technological, and behavioral factors, moderated by policy implementation, in improving hospital claim optimization under the INA-CBGs system.

Financial purity is a fundamental principle in Islamic economics that emphasizes the management of assets in a halal, fair, and responsible manner in accordance with sharia provisions. In the context of Islamic financial institutions, zakat plays a strategic role as an instrument for the purification of assets (tazkiyat al-mal) and as a mechanism for wealth redistribution to achieve social justice. This study aims to analyze the role of zakat in maintaining the financial purity of Islamic financial institutions. The research method used is a quantitative approach with an explanatory design. Data were collected through a structured questionnaire distributed to managers and related parties in Islamic financial institutions that have zakat management programs. The research variables include zakat management as the independent variable and financial purity as the dependent variable, which were analyzed using descriptive and inferential statistical techniques. The results of this study indicate that zakat management has a positive and significant impact on the financial sanctity of Islamic financial institutions, primarily through increased sharia compliance, transparency, and institutional accountability. This finding confirms that zakat serves not only as an obligatory act of worship but also as a strategic instrument in strengthening the ethics, legitimacy, and social responsibility of Islamic financial institutions. This research is expected to provide theoretical and practical contributions to the development of sustainable zakat governance in the Islamic financial system.

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.

RS at Kemayoran continues to experience low conversion of antenatal care (ANC) patients to delivery services, with a conversion rate of 6.9% in 2024. The maternity ward Bed Occupancy Rate (BOR) also remains below national standards. Preliminary assessments indicate dissatisfaction with the hospital’s healthscape, low mimetic desire reflected in limited recommendations, and suboptimal perceived value. This study examines the effects of healthscape and mimetic desire on childbirth location decisions, with perceived value tested as a mediating variable.Methods: A quantitative cross-sectional study was conducted using Structural Equation Modeling (SEM). Data were collected from 210 ANC patients at RSUD Kemayoran through structured questionnaires. Variables included healthscape, mimetic desire, perceived value, and delivery location decision. All instruments met validity and reliability criteria.Results: Healthscape and mimetic desire significantly influenced the decision to choose RSUD Kemayoran for childbirth. Healthscape did not significantly affect perceived value, whereas mimetic desire showed a significant effect. Perceived value had a significant direct effect on delivery decisions but did not mediate the relationships between healthscape or mimetic desire and delivery choice. Healthscape emerged as the most influential determinant.Conclusion: Physical healthcare environments play a critical role in childbirth location decisions. Improving healthscape quality and strengthening professional and social recommendations may enhance ANC-to-delivery conversion rates in public hospitals.

This study aimed to determine the effect of different bait types on the catch of larval shrimp (Macrobrachium lar) using a lift net and to determine the best bait type in the waters of Cijeruk Indah, Garut Regency, West Java. The method used in this study was an experimental method with nine replications. The independent variables in this study consisted of three types of bait: earthworms, fine rice husks, and pellets, while the dependent variable was the weight of the larval shrimp caught. The results showed that different bait types significantly affected the larval shrimp catch. Based on the total catch during the study, pellet bait yielded the highest yield, with a total weight of 2,316 grams. This was followed by fine rice husk bait with a total weight of 1,256 grams, and earthworm bait with the lowest yield, at 364 grams. Data analysis using ANOVA showed a significance value of 0.031 (p < 0.05), confirming a significant difference in catch responses between the three bait types. In conclusion, pellets are the most effective type of bait to use in the anco net fishing gear in catching larval shrimp at the research location.

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.

According to the latest data from WHO (World Health Organization) in 2024, there were around 1.7 billion cases of diarrhea in children worldwide which resulted in 443,832 deaths in children under 5 years of age each year, and an additional 50,851 children aged 9 years, while the country with the most diarrhea in children in the United States was 350 million cases each year and 48 million of them were caused by bacteria in food. The purpose of this study was to determine the relationship between the role of parents and the initial handling of diarrhea in toddlers aged 1-5 years. This type of research is quantitative analytical with a cross-sectional study approach. The independent variable in the study is the role of parents, while the dependent variable is the initial handling of diarrhea in toddlers aged 1-5 years. The population in this study were all children suffering from diarrhea at the Gedang Village Health Center in 2024 as many as 283 people with a sample of 74 people. The sampling technique used was the Accidental Sampling technique. This study was conducted in the Working Area of ​​the Gedang Village Health Center, Sungai Penuh City, in January-June 2025. The results showed that most 47 (63.5%) respondents had poor parental roles, and most 42 (56.8%) respondents had poor initial handling of diarrhea in toddlers aged 1-5 years, with the results of the statistical test (Chi-Square) obtained a value of p = 0.005 (p <0.05). The conclusion of the study shows that there is a relationship between the role of parents and the initial handling of diarrhea in toddlers aged 1-5 years. The researcher's suggestion from the results of the study is that it can be applied in daily nursing practice, such as providing health education regarding the first handling of diarrhea, so that the role of parents will be even better.

This study is motivated by the rapid advancement of digital marketing and the increasing influence of psychological factors in shaping consumer behaviour, particularly among Generation Z, who are highly exposed to social media and global trends in imported skincare products. This phenomenon suggests that purchase decisions are not solely driven by digital marketing strategies but are also significantly influenced by emotional drivers such as Fear of Missing Out (FoMO). Accordingly, this study aims to analyse the effects of affiliate marketing, WhatsApp status, celebrity advertising, and FoMO on the purchase intention of Generation Z consumers in Tangerang City. Specifically, the study pursues five objectives: (1) to examine the effect of affiliate marketing on purchase intention; (2) to analyse the influence of WhatsApp status on purchase intention; (3) to investigate the impact of celebrity advertising on purchase intention; (4) to evaluate the effect of FoMO on purchase intention; and (5) to assess the simultaneous effects of all independent variables on purchase intention. This study adopts a quantitative approach using a survey method, with data collected through structured questionnaires administered to 250 respondents selected via accidental sampling. Data were analysed using multiple linear regression with the aid of SPSS software to examine the relationships among variables. The findings reveal that all independent variables exert a positive and statistically significant influence on purchase intention, with FoMO emerging as the most dominant predictor. These results underscore the greater role of psychological factors relative to digital marketing strategies in driving purchase intention among Generation Z consumers.The contribution of this study lies in integrating digital marketing strategies and psychological factors into a single empirical model, while also highlighting the growing importance of interpersonal digital communication, such as WhatsApp, in contemporary marketing contexts. From a practical perspective, the findings provide managerial implications for businesses to design marketing strategies that are not only informative but also capable of creating urgency and fostering emotional engagement among consumers.    

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.  

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.  

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.

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.  

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.

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.

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.

The retail industry generates an extremely large and continuously growing volume of transactional data along with the advancement of digital technology, thereby requiring sophisticated and systematic data analysis approaches to support effective and evidence-based business decision-making. This study aims to analyze retail sales data by utilizing the Retail Sales Dataset obtained from the Kaggle platform, which consists of 100,000 transaction records and broadly represents the characteristics of retail transactions. The main focus of this study is to classify product categories and predict customer segments, including the identification of high-spending customers (high spenders), based on demographic attributes such as age and gender, as well as various transaction-related features. The research methodology includes data preprocessing, label encoding, and feature engineering to generate additional variables, including Age_Group, Is_Holiday, and Spender_Group, which are expected to enhance the predictive capability of the models. Several machine learning algorithms, namely Decision Tree, Random Forest, and XGBoost, were implemented and evaluated to compare their respective performance. The experimental results indicate that multiclass product category classification achieves relatively low accuracy, ranging from 27% to 34%. These findings suggest the high complexity of retail data and highlight the need for further model optimization, class balancing techniques, and feature refinement to improve predictive performance in future studies.

This study aims to determine the extent to which professional competence and personality competence influence teacher performance at SMAN 1 Sangatta Selatan. This research is categorized as field research using a quantitative approach. Data were collected through questionnaires to obtain responses from participants, observations to directly monitor activities, and documentation techniques to gather supporting data. The population in this study consisted of 33 teachers at SMAN 1 Sangatta Selatan. The sample was determined using the Slovin formula, resulting in 33 respondents, all of whom were teachers from the same school. To analyze the data, multiple linear regression analysis was employed. The results showed that professional competence significantly influences teacher performance. The influence of professional competence (X1) on teacher performance (Y) was 7.2%, while the influence of personality competence (X2) on teacher performance (Y) reached 4.5%. The coefficient of determination (R²) value was 0.807, indicating that 80.7% of teacher performance at SMAN 1 Sangatta Selatan is jointly influenced by professional competence (X1) and personality competence (X2), while the remaining 19.3% is influenced by other variables not examined in this study. Based on the analysis, personality competence was found to have a more significant simultaneous effect on teacher.    

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.