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This research aims to analyze the significance of the influence of personality, courage to take risks, income expectations on students' interest in entrepreneurship at Slamet Riyadi University, Surakarta. The types of data used in this research are quantitative. The data sources used are primary and secondary data. The sample in this research was 100 students at Slamet Riyadi University, Surakarta. The method used in sampling was proportional random sampling. Data collection techniques in this research used questionnaires. Test the research instrument using validity and reliability tests. The classical assumption test uses tests: multicollinearity, autocorrelation, heteroscedasticity and normality. Data analysis techniques use multiple linear regression tests, t tests, F tests, and R2. The results of the validity and reliability tests show that all statements regarding personality, courage to take risks, income expectations and interest in entrepreneurship are declared valid because the p-value is < 0.05 and reliable because Cronbach's alpha is > 0.60. The results of the classical assumption test show that all variables have passed the multicollinearity, heteroscedasticity, autocorrelation and normality tests with normal distribution. The results of the regression analysis obtained the equation Y = .612 + 0.221 X1 + 0.326 X2 + 0.556 X3 + e. The results of the t test show that personality (X₁), courage to take risks (X₂), and income expectations (X₃) have a significant effect on students' interest in entrepreneurship at Slamet Riyadi University, Surakarta. The results of the F test showed that the regression model used in this research was correct. The R² test results show that the contribution of the independent variable to the dependent variable is 45.5%, the remaining 54.5% is influenced by other factors outside the variables studied  

In the modern computing era, servers face significant challenges in data storage due to hardware failures, cyber attacks, or human errors. The problem highlighted focuses on the impact of file systems on three critical aspects: data integrity (accuracy and consistency of data without corruption), data recovery (the ability to restore data after a failure), and failure resilience (fault tolerance, such as redundancy and journaling to prevent downtime). The main issue is that traditional file systems like FAT32 or NTFS are often susceptible to fragmentation, metadata loss, or long recovery times, which can lead to data loss of up to 20-30% on enterprise servers, especially in high-traffic environments like cloud computing.A simple problem-solving process is conducted through a straightforward comparative analysis approach: (1) A literature review of popular file systems (ext4, ZFS, Btrfs); (2) Failure simulations using tools like fsck and stress testing on virtual servers (e.g., via KVM or Docker); and (3) Measuring performance metrics with benchmarking tools like Bonnie++ for I/O throughput, recovery time, and error rates. This process is designed to be simple, requiring only a virtual lab setup without expensive hardware, and is analyzed quantitatively with descriptive statistics.The solution to the problem indicates that advanced file systems like ZFS or Btrfs provide significant improvements: data integrity is up to 95% more secure through automatic checksums, data recovery is achieved in minutes through snapshots and RAID integration, and failure resilience is higher with copy-on-write features. The main recommendation is to migrate to journaling-based file systems for servers, combined with automated backups, which can reduce the risk of downtime by up to 50%. This research provides practical guidance for system administrators to enhance server reliability without excessive additional costs.

This research aims to determine the influence of tourist attractions, social media, and values on the interest in visiting the Cunca Wulang waterfall tourist village in West Manggarai Regency. This research uses a quantitative research method. The population in this study consists of all tourists who have ever visited the Cunca Wulang Waterfall Tourism Village in West Manggarai Regency. The sample in this study consists of 100 respondents. The sampling technique used in this study is purposive sampling, a sampling method based on the researcher's considerations, which is then processed using SPSS. The data collection technique in this study uses a questionnaire. The instrument testing technique in this study uses validity and reliability. And the data analysis technique in this research uses descriptive analysis, classical assumptions, multiple linear regression, coefficient of determination, and hypothesis testing. The results of this study are as follows. Based on the F-test results, an F value of 125.691 was obtained with a significance level of 0.000. This significance value is smaller than the 0.05 significance level, so it can be concluded that the regression model used in this study is statistically significant. In other words, simultaneously, the independent variables consisting of Value, Tourist Attraction, and Social Media significantly influence the dependent variable, which is the Interest in Visiting the Cunca Wulang Waterfall Tourism Village in Manggarai Barat Regency

Pregnancy can trigger a maturity crisis that can cause stress. Stress in pregnant women is related to stress during pregnancy, childbirth, and postpartum. The purpose of this study was to examine factors related to stress levels in pregnant women facing childbirth. This type of research was an analytical survey with a cross-sectional approach conducted in the Lubuk Buaya Community Health Center Work Area from April 25 to May 7, 2022. The population was all pregnant women who visited the Lubuk Buaya Community Health Center Work Area in Padang in 2022, totaling 178 people, with a sample of 64 people, using an accidental sampling technique. Data were collected using a questionnaire with a validity analysis result of r>0.267 and a reliability test with a Cronbach's Alpha value>0.7. They were processed manually, using univariate and bivariate analysis with the chi-square test. The results of the study showed that 26.6% experienced moderate stress, 37.5% had poor family support, 37.5% had poor husband support, 40.6% had trauma, 46.9% had a personal readiness level in the unprepared category, and 46.9% had a heavy activity level. There is a relationship between family support and stress levels, there is a relationship between husband support and stress levels, there is a relationship between traumatic experiences and stress levels, there is a relationship between personal readiness levels and stress levels, and there is a relationship between activity levels and stress levels.

This study aims to examine the influence of Career Motivation, Understanding of Motivation, and Family Environmental Factors on Interest in Becoming a Public Accountant. This study was conducted at Slamet Riyadi University and Sebelas Maret State University. The data used are quantitative. The data source is primary data. The entire population in this study was 1,330 accounting students at Slamet Riyadi University and Sebelas Maret State University. The sample used was 93 respondents. The sampling technique used was the Solvin equation and was tested using SPSS version 25. Data analysis techniques were descriptive tests, independent sample t-tests, validity tests, reliability tests, classical hypothesis tests, multiple linear regression tests, hypothesis tests, and model tests. The results of this study indicate that: (1) Career Motivation has a positive and significant influence on Interest in Becoming a Public Accountant, (2) Understanding of Motivation has a positive and significant influence on Interest in Becoming a Public Accountant, (3) Family Environmental Factors have a positive and significant influence on Interest in Becoming a Public Accountant

In the modern industrial world, robots like mechanical arms in automotive factories or packaging lines must move quickly and safely. For this, a real-time operating sistem (RTOS) is needed—think of it as a "super-fast brain" that ensures the robot reacts instantly to commands, without delays or errors. This paper analyzes popular RTOS like FreeRTOS and VxWorks for controlling industrial robots, focusing on evaluating performance (speed of operation) and stability (long-term reliability). We conducted tests in a lab using a simple robot that moves its arm to pick up objects. Performance was measured by response time (how quickly the robot stops when encountering an obstacle, ideally under 10 milliseconds) and throughput (how many tasks it can complete per second). Stability was checked through simulations of disruptions, like heavy loads or interfered sensor signals, using metrics such as error rate and time variation (jitter). Results show that FreeRTOS is more efficient for small, affordable robots, with high performance (average response time of 4 ms) but moderate stability (5-10% errors during overload). In contrast, VxWorks excels in stability (errors <2%, stable for up to 95% of tasks on time) for large factory robots, though it requires stronger hardware. Our analysis uses simple models like graphs and repeated tests, without complex formulas, to prove that the right RTOS can boost production efficiency by up to 25% and reduce accident risks.

Android continues to innovate, and biometric systems particularly fingerprint sensors must operate with high efficiency. However, the main challenge lies in the communication between hardware and software, which often causes high latency, excessive power consumption, and protocol incompatibility between components. As a result, authentication speed decreases and system stability is compromised, especially on mid- to low-range devices. This study explores various implementations of Android-based fingerprint systems, focusing on how sensor modules interact with the microcontroller or Trusted Execution Environment (TEE) and the operating system through a hardware-software co-design approach to evaluate integration efficiency across all layers. The analysis reveals that conventional protocols such as Bluetooth or serial connections still cause delays, while improvements in drivers and the Hardware Abstraction Layer (HAL) can significantly reduce latency. As a solution, the researchers propose a co-design optimization approach that utilizes data flow normalization within the HAL and adopts lightweight communication protocols to accelerate the verification process. Based on the test results, this approach successfully improves efficiency—authentication time is reduced by up to 35% and power consumption decreases by approximately 15%. Therefore, the efficiency of communication between hardware and software becomes a key factor in enhancing the performance and reliability of fingerprint systems on Android devices.

University students frequently face various academic demands, such as coursework, research, field practice, and examinations. These pressures may lead to psychological stress that can trigger anxiety. If not properly managed, anxiety can negatively affect academic performance, social interactions, and students’ psychological well-being. The aim of this study was to examine the relationship between the intensity of Qur’an recitation and the level of anxiety among students. This research employed a quantitative descriptive design involving 103 students from the Department of Psychology, Padang State University as participants. The sampling technique used was nonprobability sampling with a purposive sampling approach. The instruments consisted of the Qur’an Reading Intensity Scale adapted from Pradika (2014) with a reliability coefficient of 0.721, and the Zung Self-Rating Anxiety Scale with a reliability coefficient of 0.829. Data were analyzed using Pearson’s product-moment correlation test. The findings revealed a significant negative correlation between the intensity of Qur’an recitation and students’ anxiety levels (r = -0.801; p = 0.000 < 0.05). This indicates that the more frequently students read the Qur’an, the lower their anxiety levels, and vice versa. Categorization results further showed that most students had a high intensity of Qur’an recitation (42.7%) and experienced low to moderate levels of anxiety (78.7%). These results reinforce previous studies suggesting that spiritual practices such as Qur’an recitation can serve as an effective spiritual coping strategy to foster tranquility, regulate emotions, and strengthen resilience in facing academic stressors. Therefore, Qur’an recitation can be recommended as a complementary approach to maintaining students’ mental health in higher education settings.

This study aims to analyze the effect of price, promotion, and location on customer satisfaction at The Daily Wash Laundry Kediri. This research employs a quantitative associative approach to examine the causal relationship among variables. The sample consists of 170 respondents selected through purposive sampling. Data were collected using a five-point Likert scale questionnaire and analyzed through validity and reliability testing, classical assumption tests, and multiple linear regression analysis using SPSS version 26. The results show that price, promotion, and location each have a positive and significant effect on customer satisfaction. Simultaneously, the three variables significantly influence customer satisfaction with a determination coefficient value of 0.908, indicating that 90.8% of customer satisfaction variation can be explained by these variables. These findings indicate that a combination of appropriate pricing, effective promotion, and strategic location significantly enhances customer satisfaction in the modern laundry service industry.

This study aims to analyze the influence of work facilities, competence, and work conflict on employee productivity at UD Karya Pala Kediri, both partially and simultaneously. The research employed a quantitative approach with a causal associative design. The population consisted of 36 employees, all of whom were included as respondents using a saturated sampling technique. Data were collected through questionnaires using a five-point Likert scale and analyzed using validity, reliability, classical assumption tests, and multiple linear regression analysis. The results indicate that work facilities, competence, and work conflict have a positive and significant effect on work productivity, both partially and simultaneously, with a coefficient of determination (R²) value of 0.862. This means that 86.2% of the variation in work productivity is explained by these three variables, while the remaining 13.8% is influenced by other factors outside the research model. The findings highlight that improving employee productivity can be achieved through adequate work facilities, continuous competence development, and constructive conflict management within the workplace.

This study aims to investigate the impact of Instagram social media use on deviant behavior among students at Campus 3 of Mercu Buana University in Yogyakarta. The phenomenon of increased intensity of social media use among students is the main basis of this study, in which Instagram not only functions as an instrument of communication and self-expression, but also as a medium that has the potential to trigger various forms of deviant behavior, such as cyberbullying, self-image manipulation, and social norm violations. The research method used integrates quantitative methods with descriptive design and simple linear regression analysis. Data was collected through a survey distributed to 100 active student participants, whose sample was determined using a simple random sampling method. Validity and reliability tests showed that all research instruments met the criteria for validity and reliability, as reflected in a Cronbach's Alpha value of 0.946. The relationship between Instagram and deviant behavior among students is represented by the regression equation Y = 2.300X + 0.641. These findings indicate that an increase in the frequency of Instagram use correlates with an increase in the potential for students to adopt deviant behavior. It is hoped that this study can serve as a basis for improving digital literacy and educating students on the ethical use of social media in a university environment.

This study aims to analyze the influence of price, service quality, and product quality on consumer satisfaction at Herbal Medicine MSMEs in Pare, Kediri. The research uses a quantitative associative approach to explain the causal relationship between variables. Data were collected through a questionnaire distributed to 133 respondents selected using accidental sampling. The instrument was tested for validity and reliability, followed by classical assumption tests to ensure data normality, linearity, and consistency. Data analysis employed multiple linear regression using SPSS version 25, with t-test and F-test used to examine partial and simultaneous effects, and the coefficient of determination (R²) to measure model strength. The results indicate that price, service quality, and product quality significantly influence consumer satisfaction, both partially and simultaneously. Service quality and product quality have a positive and dominant impact, while price shows a negative relationship, indicating that consumers remain sensitive to pricing changes. The model explains 76.4% of the variation in consumer satisfaction, confirming that maintaining service excellence and consistent product quality are key to improving satisfaction and loyalty among herbal medicine consumers.

PT. YGI, an automotive manufacturing company, uses the Press Injection GB-36 machine in its production process. However, this machine frequently experiences failures, causing high downtime and reduced production efficiency. This study aims to identify the types of failures, determine the most critical components, and propose a maintenance system using the Reliability Centered Maintenance (RCM) approach. The method used is descriptive qualitative, involving FMEA (Failure Mode and Effect Analysis), Logic Tree Analysis (LTA), and maintenance action selection. Data were collected through observations, historical failure documentation, and interviews. The analysis results indicate that components such as the injection nozzle, heating, and clamping are the most critical, contributing over 80% of total failures based on Pareto analysis and the highest RPN values in FMEA. Proposed maintenance actions include Condition Directed and Time Directed approaches. Additionally, the maintenance system is supplemented with standard operating procedures (SOP) and routine inspection schedules to improve machine reliability and reduce production downtime. This study is expected to enhance the efficiency and productivity of the Press Injection GB-36 machine at PT. YGI through the appropriate implementation of RCM.

The rapid growth of social media has yielded vast digital traces with high potential for improving corporate forensic auditing. Their utilization, however, lags behind through technological reliability, privacy, and adherence to the law. The aim of this study is to explore effective utilization of social media digital traces in forensic auditing and develop a functional framework that lags neither behind through technological efficiency nor adherence to the law and ethics. A mixed-method design was utilized, combining quantitative machine learning analysis with qualitative document analysis and semi-structured interview insight. Quantitative data drawn from social media digital traces were processed using Random Forest algorithm with SMOTE for class balancing, while qualitative data were processed using thematic analysis. The results indicated high model performance with 91.3% accuracy and AUC-ROC of 0.94, together with three emergent themes: digital integration, ethics and privacy, and regulation and legality. The results demonstrate that digital footprints may serve as an effective early and reliable indicator for fraud detection, provided they are accompanied by clear regulatory and ethical frameworks. Its principal contribution lies in the development of an operational model that combines machine learning with legal and ethical perspectives, a new strategy which matures methodological refinement and practical application in today's forensic auditing.

The purpose of this study is to determine the effect of servant leadership on employee performance through teamwork as an intervening variable at BRIDA Jambi Province. This type of research is quantitative research. The population in this study were all employees at BRIDA Jambi Province, totaling 40 people with a research sample of 40 people. Data collection used a questionnaire that had been tested for validity and reliability. The research analysis method used descriptive statistical analysis using the Structural Equation Model (SEM), with Smart PLS 4.0 Software (Partial Least Square) as a tool to process the data. The results of this study indicate that servant leadership has a positive and significant influence on employee performance, servant leadership has a positive and significant influence on teamwork, teamwork has a positive and significant influence on employee performance, servant leadership has a positive and significant influence on employee performance through teamwork as an intervening variable.

This study aims to determine the effect of the mathematical puzzle playing method on the subtraction calculation ability of first-grade students of SDN 104202 Bandar Setia. The type of research used is a quasi-experiment with a pretest-posttest control group design. The research subjects consisted of two classes, namely class IA as the control class (22 students) and class IC as the experimental class (22 students). The research instrument was a subtraction calculation ability test that has been tested for validity and reliability. The results showed that the average posttest score of both classes was 78.86 in the control class and 84.77 in the experimental class where there was a significant difference. The independent t-test of both classes showed a significance value of 0.000 < 0.05, so the hypothesis H0 was rejected and H1 was accepted. Thus, it can be concluded that the mathematical puzzle method significantly improved the arithmetic and subtraction skills of first-grade students at SDN 104202 Bandar Setia.

This research presents the design, development, and implementation of a mini smart car prototype that operates using Internet of Things (IoT) technology. The system is built around the ESP8266 microcontroller (Amica version), which functions as the core processing unit responsible for handling Wi-Fi communication and data processing. The motion of the car is controlled by an L298 motor driver module that regulates the operation of DC motors. The entire system is powered by a 3.7-volt rechargeable battery, ensuring portability and energy efficiency. The study discusses in detail the hardware configuration, software programming, and integration of IoT-based control through a web or mobile interface. Functional testing of the prototype, named MINIOT, focuses on evaluating the responsiveness, stability, and reliability of remote control operations. The results are expected to show that the system can effectively receive and execute user commands while transmitting real-time telemetry data, such as motor status and connection indicators. This project demonstrates the feasibility of low-cost IoT-based automation for small-scale robotic applications.

The admission of patients to the Intensive Care Unit (ICU) or Intensive Cardiology Care Unit (ICCU) often occurs suddenly and under critical conditions, causing family members to experience psychological pressure such as anxiety, stress, and fear of losing their loved ones. This study aims to analyze the relationship between family knowledge and the level of anxiety among family members of patients treated in the ICU at Meuraxa General Hospital, Banda Aceh. The research employed a quantitative method with a descriptive correlational design and a cross-sectional approach. The population consisted of 114 patient families, with 35 respondents selected through purposive sampling. The instrument used was the Hamilton Anxiety Rating Scale (HARS), which demonstrated high reliability (α = 0.897). Data were collected from June 18 to July 5, 2025, and analyzed using univariate and bivariate methods with the chi-square test. The results showed that 19 respondents (54.3%) experienced moderate anxiety, while 14 respondents (40%) had low knowledge regarding ICU/ICCU care. Statistical analysis revealed a p-value of 0.005, indicating a significant relationship between family knowledge and anxiety levels. These findings highlight the importance of healthcare professionals in providing education to family members to improve understanding and help reduce anxiety during the patient’s treatment period in the ICU or ICCU.

The purpose of this study is to research how students' interest in learning about the digital age is influenced by digital media based on artificial intelligence (AI) at the Yogyakarta Administrative Management Academy (AMAYO) in Yogyakarta. Quantitative approaches are used in this research methodology. Purposive sampling strategies were utilized to get data from 75 pupils. The study tool was a questionnaire, and the data was evaluated using the validity test, reliability test, linear regression, T-test, F-test, and coefficient of determination (R²) in SPSS 26. This study suggests that digital media based on artificial intelligence (AI) has a favorable effect on students' interest in learning, with a regression coefficient of 0.920. Because the t-test yields a calculated t value of 57.031, which is greater than the t-table value of 1.666, H₀ is rejected and Ha is accepted. This suggests that students' interest in studying in the digital age at AMAYO Yogyakarta is significantly impacted by the use of digital media based on artificial intelligence (AI). The computed F value of 3252.522, which is higher than the F table of 3.97, indicates that the F-test also reveals results that need serious consideration. Additionally, the 97.8% coefficient of determination (R2) suggests that digital media based on artificial intelligence (AI) can affect students' motivation in learning, whereas 2.2% is influenced by other elements that are not within the purview of this study. According to the study's findings, AMAYO Yogyakarta students can boost their interest in learning in the digital age by utilizing digital media powered by artificial intelligence (AI).

Effective management of fixed assets plays a crucial role in maintaining the reliability and transparency of a company’s financial reporting. Errors in the capitalization process can lead to misstatements in financial statements and affect investment decisions. This study aims to analyze and forecast asset capitalization trends using the Autoregressive Integrated Moving Average (ARIMA) model. The research utilizes monthly recap data of asset capitalization recorded during the Settlement to Fixed Asset process from January 2021 to August 2025. The data were processed through several stages, including stationarity testing, model identification, parameter estimation, and model accuracy evaluation. The findings indicate that the data are stationary without differencing (d = 0). From several candidate models, ARIMA(0,0,3) was identified as the best model based on the lowest AIC value of 39.76. The selected model was then applied to predict asset capitalization values for the next ten periods, resulting in forecasts ranging from 1.12 to 1.56 trillion rupiah. Model evaluation showed a MAPE of 29.01%, which implies a moderate forecasting accuracy. Consequently, the ARIMA model can be considered a suitable analytical tool for monitoring and forecasting asset capitalization quantitatively.