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This research aims to look at Psychological Well-being in former drug addicts who are also ex-convicts. The population used was former drug addicts who were also former prisoners in Bukittinggi with 5 samples. This research uses non-parametric statistics with descriptive methods. The instrument used is an adaptation with a total of 36 items with aspects including a). Self Acceptance, b). Positive Relationship With Others, c). Autonomy d). Environmental Mastery, e). Purpoe In Life and f). Personal Growth. Based on the results of research that has been carried out, the Psychological Well-being results for the subject are in the Fair category with a percentage of 20%, High with a percentage of 60% and Very high with a percentage of 20%.      

This research investigates the implementation of Random Forest algorithms combined with Synthetic Minority Over-sampling Technique (SMOTE) to predict elementary school dropout rates in Indonesia, supporting the Indonesia Emas 2045 vision. A significant gap was identified in previous studies, which, despite utilizing artificial intelligence for dropout interventions, had not integrated temporal dimensions into data analysis. A temporal data-based classification model was developed using Indonesian Ministry of Education data from 2021-2023, incorporating lag features, delta calculations, and rolling statistics. Two models were implemented: one with SMOTE achieving 99% accuracy with perfect recall for high-risk regions, while the non-SMOTE model reached 100% accuracy. Temporal features were identified as crucial predictors, reflecting external fluctuations and annual changes impacting dropout decisions. This approach enables educational institutions to allocate resources more efficiently by prioritizing operational assistance for high-risk schools. The model's capacity to identify high-risk regions with 100% recall represents a strategic investment in strengthening Indonesia's human resource sustainability. To address the limitations of provincial aggregate data, expansion to include individual-level variables and model validation at district or school scales is recommended for future research.

This study aims to comprehensively examine the influence of the Problem-Based Learning (PBL) model integrated with the Internet of Things (IoT) on enhancing students’ problem-solving abilities in physics education. The integration of IoT into PBL is seen as a progressive approach to address the growing demand for innovative instructional strategies that promote higher-order thinking skills. A quantitative approach was adopted, utilizing a quasi-experimental design with a pretest-posttest nonequivalent control group format to assess the effectiveness of the intervention. The participants were 25 undergraduate physics students from the University of West Sulawesi, selected through saturated sampling due to the limited population size. To evaluate students’ problem-solving skills, data were collected using structured written tests designed around five key indicators: understanding the problem, describing the problem, planning the solution, executing the solution, and evaluating the results. Prior to hypothesis testing, normality of the data was assessed using the Kolmogorov-Smirnov test, followed by paired sample t-tests with IBM SPSS Statistics 23 to determine the significance of differences in pretest and posttest scores. The findings revealed a statistically significant improvement in students’ problem-solving skills following the implementation of the IoT-based PBL model, with results showing significance at the 5% level and gain scores classified as effective. These outcomes demonstrate the potential of the PBL-IoT integration to foster critical thinking and improve educational quality. Therefore, the implementation of this instructional model is recommended for physics educators seeking to enhance student engagement, problem-solving proficiency, and learning outcomes through the integration of emerging technologies.    

Basketball is a dynamic team sport that emphasizes hand coordination, requiring players to score by shooting the ball into the opponent’s hoop. The game involves five players per team and demands mastery of several fundamental technical skills, including throwing and catching, dribbling, shooting, pivoting, and lay-up techniques. One of the highest individual achievements in basketball is being named the Most Valuable Player (MVP), a title awarded to athletes who demonstrate exceptional performance during a game or tournament. This study aims to analyze the determining factors behind an athlete achieving MVP status, specifically focusing on LeBron James from the United States basketball team during the 2024 Paris Olympics final match against France. The research employs a descriptive method with data collection through document analysis, particularly using official match statistics. The assessment includes both physical performance metrics—such as points, rebounds, assists, blocks, steals, turnovers, and fouls—and psychological aspects, such as mental toughness during competition. Statistical data from the match showed that LeBron James recorded 14 points, 6 rebounds, 1 block, 10 assists, 2 steals, 5 turnovers, and 3 fouls. His shooting efficiency was also high, with a 60% field goal percentage (6/10), 62.5% on two-point shots (5/8), 50% on three-point shots (1/2), and 100% on free throws (1/1). The findings indicate that high contributions in both offensive and defensive aspects significantly influence the MVP designation. This study concludes that MVP recognition is strongly supported by measurable statistical performance and recommends that coaches integrate performance analysis technology to maximize athlete potential based on individual needs.

Bali Province has a high population density, which has the potential to affect the distribution of infectious diseases such as diarrhea. However, mapping the distribution of diarrhea cases based on population density is still limited and does not meet good cartographic principles. Therefore, this study aims to present data on the distribution of diarrhea cases based on population density in Bali Province during the 2020-2022 period. This study used an analytic observational method with a cross-sectional design. The data used were secondary data from the Bali Province Health Profile and the Central Statistics Agency (BPS) for 2020-2022. Data analysis was carried out using geographic mapping with Geographic Information Systems (GIS) and statistical tests in the form of multiple linear regression and Spearman correlation. The results showed an increase in the strength of the relationship between population density and the number of diarrhea cases, as indicated by the rho value which increased from 0.1833 in 2020 to 0.6000 in 2022. However, this relationship was not statistically significant (p-value > 0.05), indicating that population density is not the only factor contributing to the increase in diarrhea cases. Other factors such as sanitation, access to clean water, and public awareness in maintaining hygiene also play a role in the spread of this disease. Although there is a trend that an increase in population density in Bali goes hand in hand with an increase in diarrhea cases, this relationship is not statistically strong enough. Therefore, a multidisciplinary approach is needed to address diarrhea cases, including improved sanitation facilities, public health education, as well as strengthening the spatial data-based disease monitoring system.

Pneumonia remains one of the leading causes of mortality among children under five years old worldwide. Population density is presumed to be one of the factors influencing pneumonia incidence, particularly in regions with high population growth and mobility, such as Bali Province. This study aimed to analyze the relationship between population density and pneumonia incidence among under-five children in Bali Province during the 2021–2023 period. This research was a descriptive quantitative study with a correlational design. Data on population density and under-five pneumonia cases were obtained from reports by the Bali Provincial Health Office and the Central Bureau of Statistics (BPS). Spatial visualization was performed using Epi Map version 7.2.5.0, and correlation analysis was conducted using R Studio. Descriptive analysis showed an increase in both population density and the number of under-five pneumonia cases in Bali Province during 2021–2023. Population density rose from 11,641 people/km² to 12,096 people/km², while pneumonia cases increased from 2,677 to 5,743. However, Spearman correlation analysis indicated no statistically significant relationship between population density and pneumonia incidence, with rho values of 0.5667 and p-values of 0.1206 for 2021 and 2022, and a rho of 0.2333 with a p-value of 0.5517 in 2023 (p > 0.05). No significant relationship was found between population density and pneumonia incidence among children under five in Bali Province.

This research was conducted based on the phenomenon of BPK audit quality still needs to be improved when facing a lot of data with large capacity, variety, and high frequency in audit practice. One of the technological advances in facing these challenges is the emergence of big data analytics (BDA). The purpose of this study is to determine the effect of training, competence, and adoption of big data analytics on BPK audit quality. This research method is a quantitative method with a survey approach at the BPK RI office. This study uses primary data obtained through filling out an online questionnaire by 184 respondents who were sampled in the study. The data analysis method of this research is descriptive statistics and path analysis using the IBM SPSS Statistics 26 program. The results showed that training, competence, and adoption of big data analytics had a positive and significant effect on audit quality both partially and simultaneously.  

Financial problems are not only caused by low income, but financial difficulties can also arise if there are errors in financial management such as incorrect use of credit, and lack of financial planning. Therefore, financial literacy is needed for someone in managing their financial resources to be able to adjust to income and lifestyle in the modern era like today. The purpose of this study is to determine the effect of financial literacy, financial technology, financial risk, financial attitudes and financial income on financial management (study on the community of Kertasari Village, Banjarharjo District, Brebes Regency). This study uses a survey approach for its quantitative research design. The population used is the community in Kertasari Village with a population of 994 heads of families, having personal income, and being the head of the family. In determining the sample, the author uses the Slovin formula so that the number of samples obtained is 100 samples. The data analysis methods used are instrument testing, classical assumption testing, multiple linear regression testing, and hypothesis testing. The data obtained in this study were then processed using the IBM SPSS Statistics 23 program. The results of the study show that financial literacy has a positive and significant effect on financial management, financial technology has no effect on financial management, financial risk has a positive and significant effect on financial management, financial attitudes have a positive and significant effect on financial management, and financial income has a positive effect on financial management.

This study explores the self-appearance of Fashion Design students in the Family Welfare Education Department, Faculty of Engineering, Manado State University. The aim of the research is to examine the relationship between fashion knowledge and the self-appearance of these students. This is a descriptive correlational study, which provides an overview of the relationship between the variable of fashion knowledge (X) and the variable of self-appearance (Y). The population in this study consists of 50 undergraduate Fashion Design students from the 2021–2024 cohorts, with a sample size of 33 students. The sample was selected using a simple random sampling technique. The research instrument used was a questionnaire based on a Likert scale. Data analysis techniques included descriptive statistics, data quality testing, and a t-test. The results of the study reveal that there is a positive relationship between fashion knowledge and the self-appearance of Fashion Design students in the Family Welfare Education Department, Faculty of Engineering, Manado State University, with a contribution of 51.3%.

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.

This study aims to comprehensively examine the influence of the Problem-Based Learning (PBL) model integrated with the Internet of Things (IoT) on enhancing students’ problem-solving abilities in physics education. The integration of IoT into PBL is seen as a progressive approach to address the growing demand for innovative instructional strategies that promote higher-order thinking skills. A quantitative approach was adopted, utilizing a quasi-experimental design with a pretest-posttest nonequivalent control group format to assess the effectiveness of the intervention. The participants were 25 undergraduate physics students from the University of West Sulawesi, selected through saturated sampling due to the limited population size. To evaluate students’ problem-solving skills, data were collected using structured written tests designed around five key indicators: understanding the problem, describing the problem, planning the solution, executing the solution, and evaluating the results. Prior to hypothesis testing, normality of the data was assessed using the Kolmogorov-Smirnov test, followed by paired sample t-tests with IBM SPSS Statistics 23 to determine the significance of differences in pretest and posttest scores. The findings revealed a statistically significant improvement in students’ problem-solving skills following the implementation of the IoT-based PBL model, with results showing significance at the 5% level and gain scores classified as effective. These outcomes demonstrate the potential of the PBL-IoT integration to foster critical thinking and improve educational quality. Therefore, the implementation of this instructional model is recommended for physics educators seeking to enhance student engagement, problem-solving proficiency, and learning outcomes through the integration of emerging technologies.

Earnings management remains a critical topic in financial reporting, as it can mislead stakeholders and distort the actual financial performance of a company. This study aims to analyze and test the effect of deferred tax assets, deferred tax expenses, and managerial ownership on earnings management in Consumer Non-Cyclicals companies listed on the Indonesia Stock Exchange (IDX) during the 2019–2023 period. The motivation behind this research stems from the increasing concerns over the use of tax-related components and ownership structures as instruments in manipulating financial outcomes. The research employs a descriptive method with a quantitative approach, utilizing secondary data sourced from published financial statements and annual reports. The sample is selected through purposive sampling based on specific criteria, resulting in a total of 10 companies being analyzed. The analytical techniques applied include descriptive statistics, panel data regression, classical assumption tests, multiple linear regression, and hypothesis testing to ensure robust and valid results. The findings reveal that deferred tax assets do not significantly affect earnings management practices. In contrast, deferred tax expenses and managerial ownership are found to have a significant influence on earnings management. Furthermore, when tested simultaneously, deferred tax assets, deferred tax expenses, and managerial ownership collectively exhibit a significant effect on earnings management. These results imply that while not all tax-related variables influence earnings manipulation, certain components—particularly deferred tax expenses and ownership structure—play a pivotal role. This study contributes to the literature by providing empirical evidence on the relevance of tax accounting and governance mechanisms in shaping earnings quality.

This research was conducted to analyze the factors that influence the problematic financing of murabaha contract products at Islamic commercial banks in 2017-2021 with research samples of Islamic commercial banks in Islamic banking statistics published by the Financial Services Authority (OJK) and analyzed using multiple linear regression. The results of the analysis obtained a significant negative effect of murabahah financing and interest rates on problematic financing of murabahah contract products. Meanwhile, capital adequacy has a negative but not significant effect on financing problematic murabahah contract products at Islamic commercial banks in Indonesia from 2017 to 2021. So that additional capital is carried out by banks, it does not allow for a decrease in problematic financing of murabahah contract products at Islamic commercial banks.

This study is based on problems that often occur in patients at NU Mangir Hospital with the aim of this study as an effort to detect several possibilities that occur so that it becomes a solution to minimize existing symptoms. This study uses quantitative research with the type of data collection taken based on random sampling techniques from existing patients and then analyzed using statistics with the help of SPSS version 20.00. Infection in patients with Water Seal Drainage (WSD) is a serious problem that increases morbidity and mortality. This study aims to identify demographic and clinical factors that influence the incidence of infection in WSD patients at NU Mangir Hospital, Banyuwangi. The method used is a cross-sectional approach with purposive sampling of 24 respondents. The results showed that systemic infections occurred most often (45.8%), and age factors, length of WSD installation, leukocyte levels, and comorbidities were significantly related to the incidence of infection. Improvement in the quality of care is needed to reduce the risk of infection.

The 2030 Sustainable Development Goals (SDGs) to end preventable newborn and under-five deaths with all countries striving to reduce the Neonatal Mortality Rate (NMR) to 12 per 1000 live births and reduce the Toddler Mortality Rate (IMR) to 25 per 1000 live births by 2030 (UNICEF, 2020). Based on the North Sumatra Central Bureau of Statistics, pregnant women who experienced SEZ in 2021 were 2,296 pregnant women, and in 2022 there was a decrease in the incidence of SEZ of 1,383 pregnant women, and in 2023 there was another increase of 1,765 pregnant women (BPS SUMUT, 2023). The type and design of quantitative analytical research through observational with case control study design is a study used to determine risk factors or health problems that are thought to have a close relationship with diseases that occur in the community. Age affects the occurrence of complications in third trimester pregnancy at Sungai Raya Health Center, East Aceh in 2024, where the results of the chi-square statistical test on maternal age are ρ = 0.006 <0.05. Parity affects the occurrence of complications in third trimester pregnancy at the Sungai Raya Health Center of East Aceh in 2024 where the results of the chi-square statistical test on parity are ρ = 0.020 <0.05. Gestational distance affects the occurrence of complications in third trimester pregnancy at the Sungai Raya East Aceh Health Center in 2024, where the results of data analysis using the chi-square test are ρ = 0.018 <0.05.    

This study aims to analyze the relationship between the open poverty rate (TPT) and the poverty rate in Jambi City from 2014 to 2023. Poverty and poverty are important issues in regional development because they directly impact community welfare. This study employed a quantitative method with a descriptive correlational approach, and data analysis was conducted using the Pearson correlation test. Secondary data were obtained from the Jambi City Central Statistics Agency (BPS). The results of the normality test indicated that the data were normally distributed, making them suitable for analysis using Pearson. The correlation analysis showed a correlation coefficient between the TPT and poverty of 0.049 with a significance level of 0.893, indicating no significant relationship between the two variables. This finding suggests that poverty is not the sole factor determining the poverty rate in Jambi City. Therefore, poverty alleviation requires a multidimensional approach that focuses not only on employment but also includes education, distribution of social assistance, and equitable regional development.

This study aims to analyze the effect of government spending, unemployment, and inflation on the number of poor people in North Sumatra Province during the period 2001-2023. The data used is secondary data obtained from the Central Bureau of Statistics (BPS) and Bank Indonesia. The analysis method used is multiple linear regression with EViews 13 software. The classical assumption tests used include normality, multicollinearity, heteroscedasticity, and autocorrelation tests. The results show that government spending has a negative and significant effect on poverty, while unemployment and inflation have no significant effect. Simultaneously, the three variables have a significant influence on the number of poor people in North Sumatra. It is recommended that the government increase the effectiveness of spending on strategic sectors for poverty alleviation and maintain economic stability with integrated policies.

This study analyzes the human development index, regional minimum wage, and labor force participation rate on poverty in North Sumatra in 2001-2023. The data used is secondary data in the form of time series obtained from the publication of the Central Bureau of Statistics. The analysis method used is multiple regression with E-Views software. The results showed that the human development index has no effect, the regional minimum wage has a negative effect and the labor force participation rate has a negative and significant effect on poverty, which indicates that an increase in the human development index tends to not affect poverty because it has a positive value. In contrast, the regional minimum wage and labor force participation rate show a negative and significant effect on poverty. Simultaneously, the human development index, regional minimum wage and labor force participation rate have a significant effect on poverty.

Immunization is one of the important disease prevention efforts for toddlers. Complete immunization in toddlers can prevent various diseases that can be high-risk for children's health, such as diphtheria, polio, hepatitis, and measles. However, the level of complete immunization coverage in toddlers in Indonesia, including in the working area of ​​the UPTD Sawang Health Center, North Aceh Regency, is still a challenge. This study aims to identify factors that influence the implementation of complete immunization in toddlers in the area. The method used in this study is quantitative research with a descriptive approach. The research sample consisted of parents or caregivers of toddlers in the working area of ​​the UPTD Sawang Health Center, with a total of 100 respondents. Data were collected through a questionnaire that included factors such as parental knowledge, attitudes, accessibility of health services, and family socio-economic factors. Data analysis was carried out using descriptive statistics. The results of the study showed that there were several factors that influenced complete immunization in toddlers, namely parental knowledge about the importance of immunization, parental attitudes towards immunization, accessibility to health facilities, and parental education levels. Socioeconomic factors, such as family income and parental occupation, also played an important role in the success of complete immunization. In addition, there was a significant influence between the distance from the house to health facilities on the level of immunization coverage. From the results of this study, it can be concluded that efforts to increase the coverage of complete immunization in toddlers in the Sawang Health Center UPTD area need to consider these factors.

This study aims to analyze the effect of e-service quality and e-trust Whatsapp Reminder on customer loyalty of BPJS Ketenagakerjaan Banyuwangi Regency with customer satisfaction as an intervening variable. In the digital era, technology-based services are a key factor in improving customer experience, especially in social security services. This study uses a quantitative approach with a survey method involving 100 respondents of BPJS Ketenagakerjaan Banyuwangi Regency participants who have used the Whatsapp Reminder service. Data was collected through questionnaire methods and direct interview sampling and then analyzed using the Smart PLS method. This Smart PLS analysis method used to analyze data is the value of Path Coefficients, P-value, and T-Statistics. The results showed that e-service quality and e-trust Whatsapp Reminder have a positive and significant influence on customer satisfaction. In addition, customer satisfaction acts as a mediator that strengthens the relationship between e-service quality and e-trust Whatsapp Reminder on customer loyalty. Thus, improving the quality of digital services and trust in the WhatsApp Reminder system contribute directly to BPJS Ketenagakerjaan customer loyalty. These findings provide implications for service managers for BPJS Ketenagakerjaan participants to continue to improve digital service quality and build customer trust in order to maintain loyalty in the long term.