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Environmental pollution is a common problem in cities and can increase the likelihood of flooding. The purpose of this study is to analyze environmental pollution as a cause of flooding in the Pekapuran Street area, Depok City. This study applies a descriptive method with a qualitative approach. Data were obtained through observation, documentation, and literature review. Based on the results of the study, it was found that the accumulation of household waste around the drainage channels causes obstruction of water flow, which triggers flooding during rain. In addition, the shallow, mud-filled, and poorly maintained drainage conditions increase the risk of flooding. Low levels of public awareness of environmental cleanliness are also factors that exacerbate the condition. This study concludes that flooding on Pekapuran Street is influenced not only by high rainfall, but also by environmental pollution and a suboptimal drainage system. Based on this, better waste management and drainage maintenance are needed to minimize the risk of flooding in the area.

Early detection of a potential heart attack is a crucial step in preventing sudden death from heart disease. This research aims to develop an Internet of Things (IoT)-based health monitoring system capable of measuring vital body data in real time and predicting the likelihood of a heart attack from CSV data obtained from sensors, integrated through RapidMiner as learning data using a machine learning algorithm, the Support Vector Machine (SVM). The system was built using an ESP32 microcontroller connected to a MAX30102 sensor to measure heart rate and finger oxygen levels (SpO₂), as well as a DHT22 sensor to measure temperature and humidity. The resulting data is sent to the Blynk application to display real-time data according to its parameters. The initial prediction logic was developed using a rule-based method based on medical thresholds for four vital parameters. The data was then used to train an SVM model as a classification system to detect potential heart attacks. Test results showed that the system can identify abnormal conditions with a good level of accuracy and provide early warnings based on changes in vital parameters in real time. This system is expected to be an initial solution for personal health monitoring, especially for individuals at risk of heart disease. It can be further developed with cloud integration and automatic notifications to users' devices.

This study examines the relationship between organizational culture and the sustainability of public service innovation within government bureaucracy. Although many public service innovations show positive results in the initial stages, many do not sustain in the long term. This indicates the presence of fundamental factors affecting innovation sustainability, one of which is organizational culture. Organizational culture plays a role in shaping the behavior, values, and work methods of civil servants in providing services to the public. This study aims to analyze the role of organizational culture in supporting or hindering the sustainability of public service innovations. Using a Systematic Literature Review (SLR) approach, this study analyzes 20 relevant scientific articles from 2002 to 2025. The results indicate that hierarchical, rigid, and administratively-oriented organizational cultures hinder innovation sustainability. Other factors such as low leadership support, limited incentives, and resistance to change also strengthen these barriers. Conversely, an open, collaborative, and adaptive organizational culture to change enhances the likelihood of innovation sustainability. In conclusion, the success of public service innovations is greatly influenced by the organizational culture underlying the behavior of civil servants. Therefore, transforming organizational culture to be more innovative and adaptive is a strategic step to strengthen the sustainability of innovation.

This study aims to analyze the in silico profile of the compound orientin derived from the water hyacinth plant (Eichhornia crassipes) as a potential antioxidant candidate. Orientin was selected based on its chemical structure data registered in PubChem, which provides complete information regarding molecular identity, physicochemical properties, and 2D and 3D structural representations. The prediction of biological activity was conducted using PASS Online, which indicated that orientin possesses a promising likelihood of exhibiting antioxidant activity according to relevant probability values. Furthermore, the safety assessment of the compound was carried out through ProTox-II to identify potential toxicity, including toxicity class, possible hepatotoxic effects, and other predicted safety parameters. To determine its pharmacokinetic profile, pkCSM was employed to predict ADMET characteristics such as absorption, distribution, metabolism, excretion, and additional toxicity risks. The results of these analyses show that orientin demonstrates favorable potential as an antioxidant candidate, supported by predicted pharmacological properties and relatively low toxicity levels according to in silico evaluations. Therefore, orientin has promising potential for further development in subsequent in vitro and in vivo studies.

The Fréchet distribution is one of the commonly used Extreme Value Distributions (EVDs) in statistical modeling and heavy-tailed data analysis, where it plays an important role in describing product lifetimes as well as climatic and financial phenomena. The estimation of its two parameters, namely the shape parameter and the scale parameter, is traditionally based on the Maximum Likelihood Estimation (MLE) method. However, maximizing the likelihood function for this distribution involves numerical difficulties, which necessitates the use of numerical optimization methods. In this study, we propose the use of the Aquila Optimizer (AO), a recent metaheuristic algorithm inspired by the hunting behavior of eagles, as an efficient numerical tool for maximizing the likelihood function of the Fréchet distribution. The objective function was formulated as the negative log-likelihood function (-LogL), and the Aquila Optimizer was employed to obtain the optimal estimates of the distribution parameters. Several simulation experiments with different sample sizes were conducted to compare the performance of the proposed method with a conventional approach represented by the Nelder–Mead method, using the Mean Squared Error (MSE) criterion. The simulation results demonstrated that the Aquila Optimizer outperformed the Nelder–Mead algorithm in many cases, although the superiority was slight. The results also showed that both algorithms were consistent, as their MSE values decreased with increasing sample size. In addition, a practical application was carried out using real data, and the results of the survival function estimation indicated a good fit.

The rapid growth of e-commerce has intensified competition among digital businesses, making pricing and discount strategies critical in influencing consumer purchase decisions. This study aims to examine the effect of original product price and price after discount on consumer purchase decisions on e-commerce platforms. A quantitative causal research design was employed using secondary data derived from publicly available e-commerce transaction records. Data analysis was conducted through descriptive statistics, correlation analysis, and multiple linear regression to assess the partial and simultaneous effects of pricing variables on purchase decisions, which were measured using a price-based purchase decision index. The findings indicate that both original price and discounted price have a significant negative effect on consumer purchase decisions. This suggests that lower displayed and final prices increase consumers’ likelihood of making a purchase. Furthermore, the discounted price was found to exert a more dominant influence than the original price, highlighting the importance of perceived value in online purchasing behavior. This study contributes to the digital marketing literature by providing empirical evidence on pricing effects in e-commerce and offers practical insights for e-commerce platforms in designing effective and data-driven pricing and discount strategies.

Academic stress is a psychological pressure commonly experienced by final-year university students, particularly during the process of completing their undergraduate thesis. High academic demands, limited time, pressure to graduate on schedule, and various obstacles encountered during research may intensify students’ emotional burden. When left unmanaged, academic stress can escalate into more serious psychological problems, including suicidal ideation. This study aims to analyze the relationship between academic stress levels and suicidal ideation among final-year students at Universitas Islam Sultan Agung Semarang. This research employed a quantitative design with a cross-sectional approach. A total of 180 respondents were selected using a simple random sampling technique. The research instruments consisted of the Perceived Academic Stress (PAS) scale to measure academic stress levels and the Adult Suicidal Ideation Questionnaire (ASIQ) to assess suicidal ideation. Data analysis was conducted using the Spearman Rank correlation test. The results showed that the majority of students experienced high (49.4%) and very high (47.8%) levels of academic stress. Meanwhile, suicidal ideation was most commonly found in the mild category (42.8%), followed by the no-risk category (28.9%). The statistical test indicated a significance value of p = 0.021 with a correlation coefficient of r = 0.172, demonstrating a positive and significant relationship between academic stress and suicidal ideation. These findings indicate that higher levels of academic stress are associated with an increased likelihood of suicidal thoughts among final-year students. The study highlights the importance of mental health support, academic guidance, and accessible counseling services to mitigate psychological distress and reduce the risk of suicidal ideation during the thesis completion period.

This study was conducted to analyze the causes of occupational accidents and to identify potential hazards in the material cutting process at PT Kanaan Global Indonesia using the Job Safety Analysis (JSA) approach. The high number of occupational accidents, totaling 15 cases during the period of December 2024–May 2025, indicates the existence of gaps in occupational safety control in this area. Data were collected through direct observation, interviews with workers, and the collection of historical data from the Occupational Health and Safety (OHS) unit. Risk analysis was carried out using a risk matrix to determine likelihood and severity values, followed by JSA for each work stage. The results identified 25 potential hazards, consisting of 4 risks in the extreme category, 9 in the high category, 7 in the medium category, and 5 in the low category. High-risk hazards were predominantly found in roll cutting and cutting press machines, which are characterized by mechanical hazards. Control recommendations focus on the implementation of engineering controls such as the installation of guarding systems and safety light curtains, improvements in safe work procedures, and increased discipline in the use of personal protective equipment (PPE). These findings demonstrate that the JSA method provides a comprehensive overview of risk sources and serves as an effective basis for formulating occupational accident control strategies within the company.

Bullying is a form of aggressive behavior commonly experienced by adolescents and has significant impacts on both physical and mental health. Schools, as primary social environments for teenagers, often become settings where bullying occurs. Several factors contribute to this behavior, particularly peer influence, family roles, and social media use. This study aimed to analyze factors related to bullying behavior among adolescents in a junior high school, including respondent characteristics, peer influence, family roles, and social media usage, as well as their relationships with bullying behavior. This research used a quantitative approach with a cross-sectional design involving 71 eighth-grade students as respondents. Data were collected using structured questionnaires and analyzed with the Chi-Square test. The results showed significant relationships between peer factors (p=0.003), family roles (p<0.001), and social media use (p=0.001) with bullying behavior. A large proportion of respondents reported high social media usage (45.1%) and low family involvement (45.1%), while more than half (53.5%) were categorized as being at risk of engaging in bullying behavior. These findings indicate that adolescents are strongly influenced by their social environment, both offline and online. Negative peer interactions and limited family supervision can increase the likelihood of bullying behavior. In conclusion, peer factors, family roles, and social media use are significantly associated with bullying among adolescents. Therefore, collaboration between families, schools, and communities is essential through psychosocial assessments, increased family involvement, and character education programs to prevent and reduce bullying behavior.

Micro, Small, and Medium Enterprises (MSMEs) play a vital role in driving economic growth; however, their production activities frequently face uncertainty in achieving predetermined targets. Such uncertainty arises from fluctuating market demand, delays in raw material supply, labor limitations, variations in processing time, and other technical constraints. Conventional deterministic production planning methods often fail to capture these real-world risks and variations, leading to less accurate and suboptimal decisions. Therefore, a more adaptive analytical approach that incorporates probability and uncertainty is required. This study aims to analyze the probability of achieving MSME production targets using the Monte Carlo Simulation method. This method models random production conditions by generating data based on probability distributions derived from historical records. Simulations are repeated through numerous iterations to estimate possible variations in production output and measure the likelihood of meeting targets. The results indicate that Monte Carlo simulation provides more realistic and comprehensive production forecasts compared to traditional planning approaches. By understanding both the probability of success and potential risks, MSMEs can design adaptive strategies, optimize resource allocation, manage inventory more effectively, and improve overall production planning accuracy to ensure long-term business sustainability in a dynamic environment.

The development of online platforms has transformed consumer purchasing behavior, including in the culinary MSME sector. Product availability across multiple online platforms has become an important factor influencing consumers’ purchasing decisions. This study aims to analyze the effect of the availability of culinary MSME products on various online platforms on consumer purchasing decisions. This research employs a quantitative approach using an explanatory research method. Data were collected through questionnaires distributed to consumers who had purchased culinary MSME products via more than one online platform. Data analysis techniques included validity testing, reliability testing, simple linear regression analysis, and hypothesis testing (t-test). The results indicate that the availability of culinary MSME products on various online platforms has a positive and significant effect on consumer purchasing decisions. These findings suggest that the easier culinary MSME products are to find, access, and consistently available across multiple online platforms, the higher the likelihood of consumers making purchasing decisions. This study is expected to contribute theoretically to digital marketing literature and provide practical insights for culinary MSMEs in developing effective multi-platform marketing strategies.

Stock price crash risk has become a critical concern in investment decision making and risk management, drawing the attention of investors and regulators amid a dynamic global business environment and repeated financial crises. However, empirical evidence on this issue remains limited in developing countries, particularly in the Iraqi context. Therefore, this study examines the relationship between board characteristics—board gender diversity, board size, and board independence—and stock price crash risk, as well as the mediating role of audit committee effectiveness. The study uses secondary data from ten banks listed on the Iraq Stock Exchange (ISX) during the 2017–2023 period. The findings show that board gender diversity and board size significantly reduce stock price crash risk. Higher female representation on boards is associated with more conservative decision making and stronger monitoring, which improves financial reporting transparency. An appropriately sized board also enhances oversight and lowers the likelihood of extreme negative stock price movements. In addition, the results indicate that the frequency of audit committee meetings mediates the relationship between board independence and stock price crash risk, suggesting that board independence is more effective when supported by an active audit committee. This study recommends that investors and financial analysts consider board characteristics and audit committee effectiveness when assessing firm value and risk. Furthermore, regulators and policymakers are encouraged to promote gender diversity on corporate boards to strengthen governance quality and reduce the probability of stock price crashes.

Financial statements have an important role in facilitating all forms of economic activity in the private, public, and non-profit sectors. However, in reality, many companies commit financial statement fraud, causing losses to users. With the increasing attention to financial statement fraud, board diversity has become an important aspect in improving corporate financial reporting monitoring and reducing the possibility of fraud. However, previous studies on the effect of this factor on financial statement fraud still show mixed findings, particularly in the food and beverage manufacturing sub-sector in Indonesia. This study aims to analyze the effect of board diversity on financial statement fraud in food and beverage companies listed on the Indonesia Stock Exchange for the period 2021–2023. This study uses a quantitative approach with secondary data obtained from companies' annual reports and financial statements. Board diversity in this study includes board gender diversity, board age diversity, and board education diversity, all of which are measured using dummy variables. Financial statement fraud is measured using the Beneish m-score. Data analysis is performed using multiple linear regression with the Ordinary Least Squares approach. The results show that board age diversity has a significant negative effect on financial statement fraud. These findings indicate that board diversity is one of the factors that can reduce the likelihood of financial statement fraud.

This study examines the factors that cause fraud in financial reporting. The study analyzed 195 data points from 39 financial institutions listed on the Indonesia Stock Exchange (IDX) during the period 2019 to 2023 using a purposive sampling technique. The research applied multiple linear regression analysis to analyze the impact of governance independence and performance variables on the likelihood of fraudulent financial reporting. The independent variables include financial targets assessed by profitability (return on assets [ROA]), financial stability measured by changes in assets, external pressure measured by the debt-to-equity ratio (DER), and the proportion of independent commissioners as a measure of good corporate governance. The study proves that financial targets affect fraudulent financial reporting, while financial stability, external pressure, and independent commissioners do not influence fraudulent financial reporting. The findings of this study provide valuable insights for regulators, investors, and management to enhance oversight and reduce the risk of fraud in the banking sector.

Informed consent constitutes a fundamental legal and ethical requirement in healthcare services, ensuring that every medical action is performed with the patient’s full awareness and voluntary approval. In Indonesia, the obligation to obtain informed consent is firmly regulated under the Health Law No. 17 of 2023, the Minister of Health Regulation on Medical Consent, and provisions on medical records. This paper examines the essential role of informed consent as a protective instrument for both patients and healthcare providers within the clinical and legal framework. Informed consent guarantees patients’ rights to information, autonomy, and decision-making, while providing legal safeguards for medical practitioners by documenting the process of explanation, acceptance, or refusal of medical treatment. Proper documentation within medical records ensures accountability, continuity of care, and serves as crucial evidence when medical disputes arise. Medical disputes often stem from dissatisfaction, communication gaps, or misunderstandings about risks inherent in medical procedures. Therefore, informed consent functions not merely as an administrative requirement but as a mechanism for preventing conflict, clarifying responsibilities, and distinguishing unavoidable medical risks from professional negligence. By strengthening the implementation of informed consent, healthcare providers can enhance transparency, improve service quality, and reduce the likelihood of medical litigation.  

Prelabor rupture of membranes (PROM) remains one of the most frequently encountered obstetric complications and continues to contribute substantially to maternal and neonatal morbidity and mortality. Numerous factors have been associated with PROM; however, the available evidence presents considerable variation, highlighting the need to re-evaluate these determinants using recent empirical findings. This review aims to identify and synthesize the principal factors influencing PROM based on ten studies published within the last five years. A systematic search was conducted across PubMed, Scopus, Web of Science, and Google Scholar using predefined keywords, followed by screening through established eligibility criteria. Relevant data from each study including study design, geographical setting, assessed risk factors, and statistical outcomes such as odds ratios or relative risks  were extracted and compared. The review indicates that reproductive and urinary tract infections, inadequate nutritional status, high-risk obstetric history, and short interpregnancy intervals consistently emerge as major determinants. Social factors and the quality of antenatal services were also shown to heighten the likelihood of PROM. Overall, the findings emphasize that PROM arises from a combination of medical and non-medical influences, reinforcing the need for preventive strategies that adopt a comprehensive and integrated approach.

This study aims to analyze the use of interior photography as a means to preserve and visually document the FMM Convent Chapel Regina Pacis in Bogor. The chapel is a historic site with significant artistic, spiritual, and architectural value, and has been officially recognized by the central government as a cultural heritage building. The importance of this research arises from the fact that the chapel is not included in the official publication of cultural heritage buildings in Bogor City that has been identified. Its absence from this publication indicates a lack of visual documentation and historical information necessary to support conservation efforts. Insufficient documentation increases the likelihood of losing architectural value should changes or damage occur in the future. To address this issue, the study seeks to produce interior photographic documentation that accurately and clearly represents the architectural identity of the chapel. This research employs a descriptive qualitative approach, consisting of interviews with the chapel’s management, direct on-site observations, and the development of an interior photography concept that considers spatial structure, perspective, and lighting. In this context, interior photography functions not only as an aesthetic medium but also as a preservation tool capable of storing long-term information.The resulting visual documentation is expected to serve as a valuable reference for managers, researchers, and local government authorities, while also encouraging the inclusion of the Regina Pacis Chapel in the official publication of cultural heritage buildings in Bogor City. In this way, the study contributes to strengthening cultural archives and supporting the preservation of historical architecture.

This research has a purpose to determine the effect of online transaction security on purchasing decisions through the Shopee application. The respondents consisted of 74 students from the Digital Business Study Program at Universitas Amikom Purwokerto who actively use Shopee. This research employed a quantitative descriptive method with simple linear regression analysis. The results indicate that online transaction security has a positive and significant effect on purchasing decisions, with a regression coefficient of 0.887 and a significance value of 0.000. The coefficient of determination of 35.2% shows that transaction security contributes to purchasing decisions, while the remaining percentage is influenced by other factors. The higher the level of security perceived by consumers during online transactions, the greater the likelihood of making a purchase. These findings highlight the importance of improving security systems and information transparency on e-commerce platforms such as Shopee to create a safe, comfortable, and trustworthy shopping experience for users.

This study aims to forecast beef prices in Palembang City and at the national level in Indonesia using the Autoregressive Integrated Moving Average (ARIMA) method. The data used are the monthly average beef prices for the period January 2019 to December 2024. The analysis involves stationarity tests using Augmented Dickey-Fuller (ADF), model identification through Autocorrelation Function (ACF) and Partial Autocorrelation Function (PACF) plots, parameter estimation with Maximum Likelihood Estimation (MLE), and residual diagnostics with the Ljung-Box and Jarque-Bera tests. The results show that beef prices at both regional levels are not stationary at the level but become stationary after the first differencing (I(1)). The best ARIMA models obtained are ARIMA(0,1,1) for Palembang City and ARIMA(1,1,0) for the national level. Both models successfully predict price fluctuations with a low error rate and show a moderate price increase trend. These findings provide practical implications for price stabilization policy making and beef-related business planning. The forecast results state that beef prices in Palembang City and nationally are predicted to tend to rise in 2025 from January to December.  

The rapid development of communication technology has driven high demand for smartphones, including among students. Based on this, this study was formulated to answer the question: "Does brand image influence OPPO smartphone purchasing decisions among students in the Sharia Business Management Study Program at STAIN Mandailing Natal?". This study aims to analyze and measure the extent of brand image's influence on purchasing decisions. This study used a quantitative approach with a questionnaire method of 75 student respondents from the 2021-2024 intake. Data collection techniques included observation, interviews, documentation, and a Likert-type questionnaire. The primary theories used were brand image theory and purchasing decision theory. Data analysis techniques used included validity, reliability, normality, heteroscedasticity, simple linear regression analysis, partial t-test, coefficient of determination (R²), and correlation tests, all using SPSS version 25.The results showed that brand image had a positive and significant effect on OPPO smartphone purchasing decisions among college students, with a calculated t value > t table (17.504 > 1.666). This means that the more favorable students' perceptions of OPPO's brand image, the higher their likelihood of purchasing the product.