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The rapid growth of social media among university students raises concerns regarding its impact on health, particularly sleep patterns. This research investigates the link involving social media usage intensity and students’ sleep patterns. A descriptive quantitative approach was employed through a survey method involving 30 active undergraduate students from various universities in Indonesia, using a survey based on Likert items. The analysis applied Pearson’s correlation to assess the intensity and orientation of the link between variables. The results revealed a strong and affirmative link between social media engagement and sleep pattern disturbances, indicated by a correlation score of 0.655. This reflects that greater intensity in using social media is associated with increased likelihood of disrupted sleep patterns, including irregular sleep schedules, reduced sleep duration, and decreased sleep quality. These findings emphasize the importance of better digital time management and educational interventions regarding healthy sleep habits, both for students and higher education institutions.  

International trademark infringement poses a complex challenge for brand owners due to jurisdictional variations and differing legal systems across countries. This study examines available legal remedies, ranging from non-litigation dispute resolution mechanisms such as Alternative Dispute Resolution (ADR) - encompassing negotiation, mediation, and arbitration - to formal litigation in national courts. ADR offers advantages in time efficiency, cost-effectiveness, and confidentiality, while litigation provides legal certainty through binding court decisions such as injunctions and damages awards. Preventive strategies including international trademark registration through the Madrid System and cooperation with customs authorities serve as crucial proactive protection measures. Furthermore, this research analyzes judicial considerations in cross-industry trademark disputes, including assessment of trademark similarity (visual, phonetic, conceptual), reputation of well-known marks, bad faith of infringers, and potential consumer confusion. Case studies such as Louis Vuitton vs. Louis Vuitton Dak and Zara Food vs. Zara Fashion demonstrate judicial application of the likelihood of confusion principle and anti-dilution doctrine even across different industries. The research employs normative legal methodology with statutory and secondary document analysis approaches. Findings confirm that legal strategy selection must consider infringement scale, jurisdiction, and business objectives, while international trademark protection requires integration of proactive registration, legal enforcement, and comprehensive understanding of global market dynamics.

Pregnant women with poor nutritional status or Chronic Energy Deficiency (CED) are at risk of health complications for both the mother and fetus, such as low birth weight (LBW). This study aimed to determine the relationship between pregnant women with CED and the incidence of LBW at RSUD Sultan Muhammad Jamaludin I. The study used a descriptive correlational design with a retrospective approach using secondary data from medical records. The population consisted of 330 respondents, selected by total sampling technique. Univariate and bivariate analyses (Chi-square test) were performed. Most respondents were under 35 years old (66.4%), primigravida (62.0%), in their third trimester (100%), and had tertiary education (54.2%). Most did not have LBW infants (91.8%), and most were not diagnosed with CED (24.1%). Chi-square analysis showed a significant correlation (p=0.001) with an Odds Ratio of 11.566, indicating that CED significantly influences the likelihood of LBW.

Laboratories play a crucial role in ensuring patient safety, with approximately 80–90% of clinical diagnoses relying on laboratory test results. Despite their importance, laboratory errors are reported to occur in about 0.012% to 0.6% of all tests conducted. Patient safety is fundamentally a managerial responsibility that can be improved through the implementation of robust systems aimed at detecting and addressing quality deficiencies. A reactive approach to this involves incident reporting followed by root cause analysis, which helps uncover and rectify weaknesses in existing policies and procedures. Alternatively, a proactive strategy such as Failure Mode and Effects Analysis (FMEA) focuses on evaluating the entire testing process, anticipating potential adverse events, and taking preventive measures before such issues arise. This method is particularly effective for prospective risk assessment in high-risk procedures, thereby minimizing the likelihood of errors within laboratories and other areas of patient care.

The life insurance industry plays a strategic role in the national financial system, not only as a provider of protection against life risks such as premature death or critical illness, but also as an instrument of long-term fund accumulation. Increased public awareness of the importance of risk protection has driven significant growth in the number of active policies. This condition has a direct impact on the risk exposure of claims that must be carefully managed by insurance companies. One of the main challenges in risk management is to accurately estimate the number of claims in a certain period, to support premium setting, technical reserve planning, and maintain the company's financial stability. This study aims to examine the use of Poisson regression model in estimating the frequency of life insurance claims based on the number of active policies in life insurance company. The data used is simulative and represents an exponential relationship between the number of policies and claims. The model is analyzed using the Maximum Likelihood Estimation (MLE) approach and evaluated through goodness-of-fit indicators such as deviance, Pearson chi-square, log-likelihood, and Mean Squared Error (MSE). The results of the analysis show that the Poisson regression model can capture the significant relationship pattern between the number of active policies and claims, and provide accurate prediction results. Thus, Poisson regression is proven to be a relevant and applicable statistical method in supporting strategic decision-making in insurance companies, especially in the context of data-driven risk management.

This study examines the effect of liquidity, leverage, cash flow, and managerial agency cost on financial distress among manufacturing companies listed on the Indonesia Stock Exchange. Using multiple linear regression analysis, the results show that liquidity and cash flow have a significant negative effect on financial distress, indicating that firms with higher current ratios and stronger operating cash flows are less likely to experience financial difficulties. In contrast, leverage and managerial agency costs have a significant positive effect, suggesting that excessive debt and inefficient managerial spending increase the likelihood of financial distress. The coefficient of determination (R²) of 0.983 indicates that these four variables explain 98.3% of the variation in financial distress. The findings emphasize the importance of maintaining financial efficiency and controlling agency costs to enhance corporate financial stability.

Pregnancy is one of the most significant phases in a woman's life, involving both physical and psychological changes. One of the psychological factors that often arise during pregnancy is stress. Stress during pregnancy can affect both maternal health and fetal development, and may even increase the risk of preterm birth. This study aims to analyze the relationship between stress levels in pregnant women and the risk of preterm birth at the UPTD Puskesmas Saritani. The study uses a quantitative design with a descriptive approach, where data was collected from 104 pregnant women screened using the Edinburgh Postnatal Depression Scale (EPDS) and birth status recorded in the medical records of the health center. The results showed that pregnant women who experienced stress had a higher likelihood of preterm birth compared to those who did not experience stress. This study is expected to contribute to the understanding of the impact of stress on maternal and fetal health and provide a foundation for the development of health programs to detect and manage stress in pregnant women, ultimately reducing preterm birth rates.

Anemia is one of the most common health problems among pregnant women and remains a major challenge in midwifery services. Anemia in pregnancy is primarily caused by iron deficiency, which leads to decreased hemoglobin levels and poses a risk of impaired fetal growth as well as an increased likelihood of delivery complications. Anemia in pregnant women is also one of the contributing factors to the high maternal and neonatal mortality rates (Ministry of Health of the Republic of Indonesia, 2022). This study aimed to determine the effect of iron (Fe) supplement consumption patterns on the risk of anemia among pregnant women at BPM Aida Nospita, Manunggal Village, Labuhan Deli Subdistrict, Deli Serdang Regency, North Sumatra Province, in 2025. This research employed a quantitative design with a descriptive correlational approach. The population of this study comprised all pregnant women attending BPM Aida Nospita in Manunggal Village, Labuhan Deli Subdistrict, Deli Serdang Regency, North Sumatra Province, totaling 45 participants. The results of the analysis indicated a significant relationship between the pattern of iron (Fe) supplement consumption and the risk of anemia in pregnant women (p = 0.000).

This research aims to estimate the reliability function of the Rayleigh distribution Under Type-II-Censored Data, which represents. The time of the machine's operation until the failure, and three methods were chosen to estimate the reliability function, which are, the maximum likelihood method, the momentary method, and the least squares method. As the values of the reliability function were calculated for real data related to the machines of theof the machines of Baghdad Pepsi Cola Company, and the comparison was made between the methods of estimating reliability by choosing the largest arithmetic mean for the reliability of the machines, and the greatest possibility appeared the best method, and the researcher concluded that the average times working until holidays is (4) months with a reliability of 87%.

This study looks at bad debt resolution strategies and their effect on the financial performance of Semerbak Citra Wangon Saving and Loan Cooperative (KSP) using the SPACE Matrix technique. The financial stability of cooperatives is severely threatened by bad debts, which can reduce liquidity and profitability. The four main dimensions of the SPACE Matrix approach - industry strength (IS), environmental stability (ES), competitive advantage (CA), and financial strength (FS) - were used to evaluate the cooperative's strategic position. The conclusion of the analysis, which places the cooperative in the aggressive quadrant (coordinates 5.00, 2.67), indicates that the cooperative has significant internal strengths and outward growth potential. Some recommended strategies include improved market segmentation, longer loan periods, liability restructuring, and lower interest rates. These strategies are expected to improve the cooperative's long-term financial stability and reduce the likelihood of bad debts.

Stunting is a condition of growth failure in toddlers due to chronic malnutrition that occurs over a long period of time, especially in the first 1,000 days of life. Several major risk factors for stunting that are often found in Posyandu include the nutritional status of pregnant women, parenting patterns, exclusive breastfeeding, and environmental sanitation. To analyze the Identification of Risk Factors for Stunting in Toddlers: A Study in the Working Area of ​​the Aek Godang Health Center, North Padang Lawas. The type of observational study with a cross-sectional design, the study population was 139 people. This study used samples from all mothers who had stunted toddlers in Hulu Sihapas District, North Padang Lawas Regency, with the total sampling method. Data collection used a research questionnaire. Data were analyzed univariately, bivariate (chi-square), and multivariate (logistic regression) with the enter method. Newborn weight (p = 0.001) and healthy toilets (p = 0.001) significantly influenced the risk of stunting, with low birth weight and poor sanitation increasing the risk of growth disorders in toddlers. This study shows that newborn weight (p = 0.001) and healthy toilets (p = 0.001) have a significant effect on the risk of stunting in toddlers. Babies with low birth weight and environments with poor sanitation increase the likelihood of stunting. More attention is needed to monitor newborn weight and increase access to healthy latrines to reduce the prevalence of stunting. The government and health workers are expected to strengthen nutrition and sanitation programs at the community level. 

Generation Z has emerged as a major force in today’s workforce, known for their enthusiasm in building careers and making meaningful contributions. They tend to favor flexible job environments that align with their skill sets. Despite this, many of them face job-related stress that leads to a higher likelihood of resignation. This study adopts a literature review method, analyzing 15 scholarly articles to explore the correlation between job stress and turnover intention among Generation Z employees in the creative industry. The findings reveal a significant positive relationship between stress and turnover intention, while job satisfaction and work environment help reduce the desire to quit. Key stressors include excessive workload, lack of appreciation, and mismatch between expectations and job reality. Thus, companies are encouraged to foster a supportive workplace culture and offer appropriate compensation to retain their young workforce.

This study aims to analyze the influence of digital transformation and change management on the performance of investigators at the Ditreskrimum Polda Bali in implementing the Electronic Investigation Management (E-MP) application. The research focuses on understanding the extent to which these factors affect investigative effectiveness and identifying key drivers of investigator performance improvement in a digital system. A quantitative approach was employed using a survey method. Data were collected from 128 investigators at Ditreskrimum Polda Bali through questionnaires and analyzed using multinomial logistic regression. The analysis included the Likelihood Ratio Test, Wald Test, and Pseudo R-Square to assess model significance and explanatory power. Principal Component Analysis (PCA) was applied to address multicollinearity and enhance regression model stability. The findings indicate that digital transformation and change management significantly influence investigator performance. The Nagelkerke R-Square value of 0.866 suggests that the model explains 86.6% of variability in investigator performance. Furthermore, the Likelihood Ratio Test results confirm that predictor variables have a significant impact on the dependent variable with a p-value < 0.05. the regression equation is as follows ln(P(Y=0)P(Y=1))=β0+β1X1+β2X2. In conclusion, effective implementation of digital transformation and change management positively contributes to improved investigator performance in the use of E-MP. Therefore, enhancing digital technology training and strengthening change management strategies are highly recommended to optimize the utilization of E-MP in investigative environments.

TikTok has become one of the most popular social media platforms with more than 2 billion monthly active users. This makes TikTok a very potential digital marketing tool for various brands and products. One of those TikTok accounts is @hedonestate, an account from a culinary brand that is currently a hit among generation Z with more than 40 thousand followers. This research aims to formulate the right content and engagement management strategy on the @hedonestate TikTok account in order to increase brand awareness and sales of promoted products. The research method used is a qualitative approach with a case study on the @hedonestate account. Data collection is carried out through in-depth interviews with the @hedonestate account manager and a number of his followers, as well as content analysis of the 50 latest TikTok videos uploaded to the account. The data obtained is then analyzed qualitatively to produce content strategy recommendations that are in accordance with the Elaboration Likelihood Model theory, as well as engagement strategies to increase user engagement such as the number of likes, comments, and shares so that it has the potential to encourage product purchase decisions. The results of this research are expected to provide recommendations for effective social media marketing management strategies on the TikTok account @hedonestate, so that it can increase brand awareness and sales of promoted products.

This study analyzes the influence of Augmented Reality (AR) technology on consumer purchase intention with customer engagement as an intervening variable at Sephora Indonesia. This quantitative research involved 150 respondents who are users of Sephora Virtual Artist, analyzed using Structural Equation Modeling (SEM). The research instrument measures three main variables: Augmented Reality (interactivity, vividness, novelty), Customer Engagement (cognitive, emotional, behavioral), and Purchase Intention (intention, willingness, likelihood to purchase) using a five-point Likert scale. The research results show that AR has a positive and significant effect on customer engagement and purchase intention. Customer engagement also has a positive effect on purchase intention and is proven to mediate the relationship between AR and purchase intention. This study contributes to the AR literature in beauty e-commerce and recommends that Sephora optimize AR features, develop comprehensive customer engagement strategies, and continue investing in AR technology as a competitive advantage.

Rainfall potential analysis plays a critical role in the management of air resources, mitigation of hydrometeorological disasters, and agricultural activity planning. Accurate estimation of rainfall patterns is essential to ensure effective decision-making in irrigation systems, water resource management, and disaster risk reduction strategies. This study aims to model the probability of rainfall occurrence using a statistical approach based on historical data obtained from the Bureau of Meteorology. The data spans a multi-year period and captures seasonal and regional variability in rainfall events. To characterize rainfall patterns, various probability distributions are tested, including the exponential distribution and the Weibull distribution, which are commonly applied in hydrological studies. Furthermore, the Markov chain method is employed to assess the likelihood of rainfall occurrence on a given day based on the conditions of the preceding day, thereby capturing temporal dependencies. Parameter estimation is conducted using Maximum Likelihood Estimation (MLE), a robust statistical method that enhances the precision of the model. The suitability of each probability distribution in representing the observed rainfall data is evaluated through goodness-of-fit tests such as the Kolmogorov-Smirnov test. The findings reveal that certain distributions align more closely with the local rainfall characteristics, demonstrating the importance of regional analysis in climate modeling. The combination of probabilistic modeling, Markov analysis, and rigorous statistical testing provides a reliable framework for forecasting rainfall. These results are expected to serve as a scientific basis for stakeholders in agriculture, environmental planning, and disaster preparedness, offering insights that support sustainable water resource utilization and risk management.

The impact of social media on Generation Z has resulted in the development of self-perception standards based on influencers' appearance. Body dysmorphic disorder (BDD) is characterized by individuals' negative thoughts about their physical appearance. Individuals with positive self-esteem and body image are less likely to experience body-related disorders. This study aims to examine the impact of body image and self-esteem on the tendency of BDD among young adults. The study utilized a quantitative approach, employing a multiple linear regression analysis on data collected from young adults. The findings of the study revealed a significant negative relationship between self-esteem and BDD, indicating that higher self-esteem is associated with lower BDD tendencies. Furthermore, body image was also found to have a significant impact on BDD. The study concludes that both self-esteem and body image play crucial roles in influencing the likelihood of BDD development, with self-esteem having a greater impact. These findings highlight the importance of promoting positive body image and self-esteem in order to mitigate the prevalence of BDD among young adults.    

This study explores the application of the normal distribution in analyzing the height data of Mathematics Education students at FMIPA Universitas Negeri Medan in 2024. Employing a quantitative descriptive-analytic methodology, the research involved collecting primary data from 10 randomly selected students through a questionnaire-based survey. Descriptive statistical analysis revealed a mean height of 161.4 cm with a standard deviation of 8.79 cm. The median height was found to be 164 cm, while the mode was 150 cm, indicating a slightly skewed distribution. To assess the suitability of the normal distribution model, the Shapiro-Wilk test was applied, resulting in a W value of 0.921 and a p-value of 0.361, which exceeds the 0.05 significance level. This confirms that the sample data follow a normal distribution pattern. The findings were further supported through visual representation using histograms and analysis based on the empirical rule, which showed that approximately 68% of the students' heights fall within one standard deviation of the mean (152.81–169.99 cm). Additionally, probability calculations demonstrated that the likelihood of a student being 160 cm tall or shorter is approximately 43.64%. These results validate the effectiveness of the normal distribution as a tool for analyzing biological or physical characteristics, even in small sample sizes. However, the study acknowledges its limitation in terms of sample size and suggests that future research involve larger and more diverse populations to enhance generalizability. The study highlights the relevance of normal distribution in statistical modeling, particularly for educational and health-related data interpretation and decision-making processes.

The medical committee is a non-structural body whose members are selected from among the heads of functional medical staff (SMF) or those representing SMF in the hospital. Objective : This study aims to evaluate the role of the nursing medical committee and its influence on the quality of inpatient services at Labuang Baji Hospital Makassar. Method : Analytic descriptive method with the design used crosssectional design Result : Logistic regression analysis showed a significant influence between the role of the medical committee and the quality of inpatient services with a value of p=0.002. Further quality of inpatient services with a value of p=0.002. Further logistic regression analysis showed that the role of the medical committee had a very large influence on service quality, with an Exp(B) value of 44,000. This indicates that each increase in the role of the medical committee can increase the likelihood of good service quality by 44 times. Overall, the results of this study indicate that the role of the nursing medical committee is very influential in improving the quality of inpatient services at Labuang Baji Hospital Makassar. This finding is expected to be the basis for developing strategies to improve service quality in the hospital. Suggestion : Ensure that the roles and responsibilities of the medical committee and nurses are clear and mutually supportiveThe medical committee should have a deep understanding of the care process, while nurses need to know how the role of the medical committee can influence and support their practice.

The implementation of Financial Accounting Standards Statement (PSAK) 116, which replaces PSAK 30, aims to enhance financial statement transparency by eliminating off-balance sheet transactions. This study reviews the literature on the impact of PSAK 116 on earnings management practices. The literature review findings reveal differing results across studies; some indicate that PSAK 116 improves transparency and reduces earnings management, while others suggest that PSAK 116 instead encourages earnings management to maintain certain financial ratios. Factors such as firm size, industry sector, regulatory environment, and corporate governance influence how PSAK 116 affects managerial behavior. The implications of this study highlight the importance of oversight and additional regulations to minimize the likelihood of financial statement manipulation, as well as the need for further research to understand the impact of PSAK 116 across various industry contexts and business environments.