Publication Search

Subcutaneous fat deposition is a key factor influencing overall health, playing a significant role in metabolic regulation, energy balance, and the risk of chronic diseases such as obesity and cardiovascular conditions. Understanding and accurately predicting subcutaneous fat accumulation is critical for early intervention and effective management of these health risks. This study aims to analyze the correlation between hemoglobin levels, uric acid, and anthropometric parameters as predictors of subcutaneous fat deposition in elderly individuals. A cross-sectional study was conducted on 32 elderly participants at St. Asisi Church. Anthropometric measurements, including body weight, height, muscle composition, and circumferences, were assessed using OMRON Body Composition Monitor HBF-375, elastic tape and GEA Medical HT721. Biochemical tests for hemoglobin and uric acid levels were performed using Fora 6 Plus. Spearman correlation analysis was used to evaluate the relationship between these variables and subcutaneous fat deposition. Body weight, upper arm circumference, abdominal circumference, and calf circumference showed strong positive correlations with subcutaneous fat (r>0.9, p<0.001). Skeletal muscle percentage exhibited a negative correlation with fat accumulation. Hemoglobin and uric acid levels had weaker correlations, suggesting more complex metabolic interactions. Anthropometric parameters serve as strong predictors of subcutaneous fat deposition in elderly individuals, while hemoglobin and uric acid levels show limited predictive capability.

In geotechnical engineering, building robust structures is crucial to ensure the bearing capacity of structures against external forces, so making sure soil strength and unreliable build cost and duration prediction are also very important and preliminary aspects of any construction project. Therefore, in this first-of-its-kind modern examine, the capability of various artificially intelligent (AI)-based models toward reliable forecasting and estimation of preliminary construction expenses, duration, and strength at shear is explored. First, background information about the revolutionary artificial intelligence (AI) technique along with its many distinct models ideal for geotechnical and building engineering problems is presented, The use of AI-based models in the literature for the aforementioned construction and maintenance applications is discussed in a number of current works, together with their benefits, drawbacks, and future directions. Several important input elements that significantly affect the preliminary price of construction, construction time, and soil's shear strength estimation are listed and given through analysis. Finally, some obstacles to employing AI-based models for precise forecasts in these applications are discussed, along with elements influencing the problems with cost overruns. Thus, this work can help civil engineers make effective use of artificial intelligence (AI) to solve difficult and risky tasks. It can also be used to Internet of Things (IoT) environments for self-learning applications like smart architectural health-monitoring systems

Background: Maternal nutritional status plays a crucial role in determining both maternal and neonatal health outcomes. According to data from the Indonesian Ministry of Health (2021), the prevalence of anemia among pregnant women reached 48.9%, while in Gorontalo Province, around 30% experienced malnutrition. Poor nutritional status during pregnancy is associated with increased risks of complications, including preterm birth, low birth weight, and higher maternal and neonatal mortality rates. Therefore, nutrition education is considered an essential strategy to enhance knowledge and promote adequate dietary intake among pregnant women.Objective: This study aimed to evaluate the effectiveness of nutrition education in improving the knowledge and nutritional status of pregnant women at the South Bulango Community Health Center. Methods: A quantitative study with a pre-experimental design was conducted involving 30 pregnant women selected through purposive sampling. Inclusion criteria included women aged 18–35 years, free from severe comorbidities, and willing to participate. Data were collected using questionnaires to assess nutritional knowledge, interviews to explore dietary patterns, and anthropometric measurements such as weight, height, and mid-upper arm circumference (MUAC). Data analysis employed descriptive statistics and the Wilcoxon test to assess differences before and after the intervention. Results: Most participants were aged 20–35 years (66.6%), had secondary education (63.3%), and were housewives (60%). Post-intervention results showed a substantial increase in good nutritional knowledge from 13.3% to 60%. Nutritional status also improved progressively across trimesters, with normal MUAC increasing from 33.3% to 60%, while undernutrition declined from 50% to 13.3%. The Wilcoxon test indicated a significant difference (p = 0.000; p < 0.05). Conclusion: Nutrition education effectively enhances both knowledge and nutritional status among pregnant women and should be integrated into routine antenatal care services.

Background: Tembuku Village has been recorded as having the highest number of non-contraceptive users in Bangli Regency, with a total of 815 individuals. Among them, 174 women (21.3%) are women of reproductive age (WRA) over 35 years old who do not use contraception. This age group falls under the “Four Too” category, which poses a high risk for maternal and infant mortality. Purpose: This study aims to describe the factors influencing the decision of WRA over 35 years old not to use contraception in the working area of Puskesmas Tembuku II. Method: A descriptive method was employed, with a population of 174 women. A total of 119 respondents were selected using stratified sampling. Data were collected through questionnaires and analyzed using univariate analysis. Result: The results showed that most respondents had a basic level of education, were multigravida, had household incomes below the regional minimum wage, and possessed moderate knowledge about family planning. However, more than half held unfavorable attitudes toward contraceptive use. The main factors influencing the decision not to use contraception were education level, parity, household income, and attitude. Conclusion: Unfavorable (negative) attitudes towards contraception are the main factor inhibiting the use of family planning,Therefore, health workers are expected to provide more communicative and easily understood education to increase awareness and participation in contraception use among women over 35 years old

Currently, Indonesia faces three major nutrition-related problems among adolescents, known as the triple burden of malnutrition, namely undernutrition (stunting and wasting), micronutrient deficiencies, and obesity. Children's cognitive development is greatly influenced by adequate nutrition, as physical and brain growth go hand in hand in the growth and development process. A balanced and high-quality diet supports optimal growth and development and influences children's nutritional status and intellectual intelligence. This study aims to analyze the relationship between nutritional status and intellectual intelligence in students. This study is an observational analytical study with a cross-sectional approach. The subjects of this study were 68 students aged 13–15 years at SMPN 2 Sumber, Probolinggo Regency. Primary data were obtained through IQ tests and weight and height measurements, while secondary data were in the form of student identities. Data analysis used a two-sample t-test. The results showed that out of 42 students with poor nutritional status, 38 students (90.5%) had low IQ (<100). Among 23 students with normal nutritional status, 11 students (47.8%) had low IQ and 12 students (52.2%) had moderate IQ (100–109). The statistical test results showed a p-value of 0.000 (p < 0.05), indicating a significant relationship between nutritional status and intellectual ability. In conclusion, nutritional status is associated with intellectual ability among students at SMPN 2 Sumber, Probolinggo District. Students with poor nutritional status have a higher risk of having an IQ below average.

This research was made to examine the determinants of financial performance of banking companies in Indonesia. There are four independent variables (board of diversity, net interest margin, operational efficiency, and liquidity risk) and a moderating variable (firm size) have been analyzed in this research. Testing the interaction effect of firm size in explaining the influence of these four independent variables on banking financial performance is still very limited. This quantitative research was analyzed by using secondary data from audited annual reports of the company. The purposive sampling technique was used to choose the research’s samples during the observation periods (2018-2022) and obtained 200 observations (40 samples over 5 years of research). Panel data regression with the EViews program was used to test the eight hypotheses which was developed in this research. The results of the Chow test and Hausman test confirm the use of the Random Effect Model in the analysis. The findings from testing the interaction model show that firm size does not moderate the influence of board of diversity and net interest margin on financial performance, while for operational efficiency and liquidity risk variables, the firm size shows a pure moderating role for the both.

This study examines the legal consequences and liability arising from actions taken by the Board of Directors and the Board of Commissioners of a limited liability company (Perseroan Terbatas PT) after their official terms of office have expired. Employing a cross-sectional quantitative survey design, a Likert-scale questionnaire was distributed to 270 respondent comprising corporate managers of publicly listed companies on the Indonesia Stock Exchange (large-, mid-, and small-cap) and corporate law practitioners in Greater Jakarta. Construct validity (KMO = 0.68; Bartlett’s Test p < 0.001) and reliability (Cronbach’s α = 0.78–0.84) confirmed the adequacy of the instrument. Descriptive analysis showed moderate mean scores for legal status of actions (Mean = 3.12) and reappointment mechanisms (Mean = 2.75). Pearson’s correlation revealed a significant positive relationship between “ultra vires” actions and civil liability risk (r = 0.582; p < 0.001) as well as criminal liability risk (r = 0.314; p < 0.001), whereas reappointment via the General Meeting of Shareholders (RUPS) correlated negatively with civil (r = –0.423; p < 0.001) and criminal (r = –0.287; p < 0.001) risks. Multiple linear regression reinforced these findings (R² = 0.52 for civil risk; R² = 0.31 for criminal risk). ANOVA indicated that small-cap firms faced the highest civil risk and that practitioners with over ten years of experience reported the lowest concern for criminal risk. These results underscore the need for proactive RUPS scheduling, multi-layered authorization systems, and strengthened compliance functions to mitigate ultra vires risks and reinforce good corporate governance.

The protection of personal data privacy rights has become a crucial issue in the digital age. This research aims to analyze the effectiveness of digital applications in increasing public awareness regarding the importance of personal data protection and its legal implications. The research method employed is a literature study with a normative juridical approach, analyzing relevant laws and regulations on personal data protection, literature studies, and an analysis of the features of digital applications that focus on privacy education and control. The results of the study indicate that digital applications have significant potential in raising public awareness through the provision of easily accessible information, visualization of risks, and consent control mechanisms for data usage. However, their effectiveness heavily relies on intuitive interface design, clear and concise information delivery, and developers' compliance with personal data protection principles. This research recommends the need for more comprehensive regulations to ensure the quality standards and accountability of digital applications in educating the public about personal data privacy rights, as well as encouraging collaboration between developers, the government, and civil society organizations to create a safer and more privacy-aware digital ecosystem.

This study aims to analyze the impact of solvency, profitability, and liquidity on financial distress, with good corporate governance as a moderating variable. The research employs a quantitative approach with moderation regression analysis. The results indicate that solvency, profitability, and liquidity have a significant negative effect on financial distress, meaning that the better a company's financial condition in these aspects, the lower the potential for financial difficulties. Additionally, good corporate governance is proven to moderate the effect of solvency, profitability, and liquidity on financial distress, indicating that the application of good governance strengthens the negative relationship between these financial indicators and financial distress. These findings highlight the importance of corporate management in maintaining financial health and applying good corporate governance principles to minimize the risk of financial distress.

This study explores the impact of separating audit and risk committees on financial reporting quality, emphasizing regulatory reforms introduced following the 2007–2009 financial crisis. Employing a qualitative literature review methodology, the research synthesizes findings from prior studies to evaluate the efficacy of these reforms in enhancing financial transparency and mitigating audit failures. The analysis reveals mixed outcomes, with evidence supporting the improved independence and oversight capabilities of segregated committees, while highlighting challenges such as resource constraints and evolving regulatory compliance demands. Comparative insights underscore variations across jurisdictions, emphasizing the importance of contextualizing governance practices. The study concludes with a discussion on the implications for policy and practice, alongside identified limitations and avenues for future research.

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 examine the investment performance of the Financial Institution Pension Fund (DPLK) and the associated challenges, utilizing investment performance data analysis. The findings indicate that the aggregate return on investment for DPLK over the past six years (2019-2024) has reached 6.09%. This is lower than the industry average of 6.99% during the same period. The annual investment performance of DPLK shows the following: 6.18% in 2024, 5.88% in 2023, 3.41% in 2022, 4.06% in 2021, 8.89% in 2020, and 8.17% in 2019. Despite some fluctuations, these results are still considered suboptimal. Key challenges facing DPLK include market volatility, interest rate risk, longevity risk (longer participant lifespan), balancing return and risk, regulatory compliance, inflation, limited education and financial literacy, changing investment trends, and human resource competencies. To improve performance, DPLK must enhance its investment management quality by addressing these challenges and adopting strategies that optimize returns while managing risks.

Diabetes mellitus is a chronic disease that requires proper management, including the use of conventional and alternative medicines such as herbal medicines. Patient knowledge about the benefits, risks, and potential interactions of herbal medicines with conventional medicines is very important to prevent complications. Objective This study aims to describe the level of knowledge of diabetes patients about the use of herbal medicines, including the benefits, risks, and interactions with conventional medicines at the Kebondalem Health Center, Pemalang Regency. This study uses descriptive observational analytic Data were collected through questionnaires distributed to diabetes patients who were treated at the Kebondalem Health Center. Data analysis was carried out quantitatively with percentages to measure the level of patient knowledge.

Background: According to data from the World Health Organization (WHO, 2023), antepartum hemorrhage, especially placenta previa, accounts for 15% to 20% of maternal deaths. Placenta In addition, previa accounts for 3% of all maternal deaths in Indonesia due to bleeding. Abnormal implantation of placental tissue above the endocervical os is a characteristic of placenta previa. Parity, age, endometrial hypoplasia, tumors, slow luteal response, endometrial abnormalities, history of cesarean section, curettage, multiple pregnancies, and history of placenta previa in previous pregnancies are some of the factors that can increase the risk of placenta previa. Research Objective: This is to determine the characteristics of pregnant women with the incidence of placenta previa in pregnant women at the HKBP Balige Hospital in 2024. Research Method: This is analytical with a cross-sectional design. The sampling technique uses total sampling with a sample size of 45 people. The entire data processing and analysis process uses the SPSS application. Research Results: The characteristics of pregnant women were obtained as follows: the majority of the age at risk (<20 and >35 years) as much as 55.6%; the majority of parity >3 as much as 53.3%, the majority of Ever CS as much as 60%. Results: statistical tests showed a significant correlation with the characteristics of pregnant women with age (p = 0.007), parity (p = 0.031) and history of CS (p = 0.001). Suggestion: It is expected to facilitate health workers in increasing knowledge and skills through training in maternal and neonatal emergency services as an effort to prevent complications in the mother and fetus.

This research aims to evaluate Mixue's corporate communication methods to create a positive perception of the wider audience. In this digital era, corporate image is one of the assets that affect the trust of customers. This research uses a qualitative approach based on critical analysis. The results show that the Mixue company uses several communication strategies, such as utilizing social media, open communication and transparency, cooperation with influencers, and using mascots as branding. These strategies help the brand's good reputation in the eyes of the public. It is hoped that this research will help develop corporate communication theory as well as provide practical examples of how a company builds and creates an image using good and effective strategies.

This study explores the legal responsibilities of notaries in reporting suspicious financial transactions as part of implementing the Know Your Customer (KYC) Principle. As public officials, notaries are bound by confidentiality obligations; however, in the context of anti-money laundering and counter-terrorism financing efforts, they are also required to report suspicious activities. The research applies a normative juridical approach using qualitative methods that focus on legal document analysis. The findings indicate that the notary's reporting obligation does not violate the confidentiality principle, as it is protected by law through both preventive and repressive legal safeguards. Proper implementation of the KYC Principle and due diligence allows notaries to actively contribute to financial integrity while minimizing their legal risk.

This study aims to analyze and visualize the distribution of COVID-19 cases in Indonesia throughout 2020 with a spatial-based quantitative approach. The data used was obtained from the official report of the Ministry of Health of the Republic of Indonesia as of December 30, 2020, including the number of confirmed cases, recovered, and died. The analysis was carried out by integrating clustering methods and Geographic Information Systems (GIS) using Quantum GIS (QGIS) software. The visualization results show significant spatial variations between provinces, where provinces with high population density such as DKI Jakarta, West Java, East Java, and Central Java are recorded as areas with the highest caseload. In addition, areas with limited health facilities also show a high potential risk of transmission and death. Cluster patterns of positive and cured cases generally show similarities, while mortality rates show spatial inequalities that are important to look at. These findings emphasize the importance of spatial data integration in area-based policy planning for pandemic control. Spatial visualization not only facilitates understanding of distribution patterns, but also supports more effective and targeted decision-making.

Based on observations, several cases of Needle Stick Injury (NSI) were found in nurses in the inpatient unit of RSUD H. Abdul Manap Jambi City during the vulnerable years 2022 to 2024. The risk of Needle Stick Injury (NSI) can cause infections such as HBV (Hepatitis B), HCV (Hepatitis C), and HIV (Human Immunodeficiency Virus). The purpose of this study was to determine the factors associated with the incidence of NSI in nurses in the inpatient unit of RSUD H. Abdul Manap Jambi City. This study is a quantitative study using an analytic survey with a cross sectional approach. The instruments used were structured questionnaires and observation sheets that were prepared based on literature review and had been tested for validity and reliability. This instrument selection was carried out to obtain data in accordance with the research objectives. The population in this study were 78 executive nurses in the inpatient unit with sampling using sampling techniques (total sampling). Data analysis used the chi-squre test to identify the determinants of the incidence of NSI. The results of this study showed the incidence of Needle Stick Injury (NSI) in nurses in the inpatient unit of RSUD H. Abdul Manap Jambi City who had experienced (43.6%) and who had not (56.4%). There is a relationship between K3 training and the incidence of Needle Stick Injury (NSI) (p = 0.000), work shifts with the incidence of NSI (p = 0.000), and there is no relationship between the use of PPE with the incidence of NSI (p = 0.278). It is concluded that there is a relationship between the incidence of Needle Stick Injury (NSI) in nurses at the inpatient unit of RSUD H. Abdul Manap Jambi City, namely K3 training and work shifts. While those that are not related, namely the use of PPE because it is not statistically significant.

Hypertension is a condition marked by elevated blood pressure, increasing risks of morbidity and mortality. Non-pharmacological treatments such as Tera exercise and acupressure therapy at the Taichong point offer alternative interventions. Tera exercise combines breathing techniques and body movements to reduce anxiety and promote vasodilation, thereby lowering blood pressure. Acupressure at the Taichong point facilitates energy flow, also contributing to blood pressure reduction. This study aims to compare the effectiveness of Tera exercise and Taichong point acupressure in lowering blood pressure among hypertensive patients. A two-group pre-post design was employed with a sample of 44 respondents selected through purposive sampling. Blood pressure data were collected using observation sheets. In the Tera exercise group (n=22), the average systolic pressure decreased from 148.77 mmHg to 143.77 mmHg, and diastolic pressure from 88.00 mmHg to 83.00 mmHg. In the acupressure group (n=22), systolic pressure reduced from 153.36 mmHg to 147.50 mmHg, and diastolic from 92.86 mmHg to 84.00 mmHg. Paired t-test analysis showed a significant difference (p-value = 0.000 < α = 0.05), indicating that acupressure therapy at the Taichong point is more effective in reducing blood pressure. This study concludes that while both therapies are effective, acupressure yields greater reductions and is recommended as a non-pharmacological treatment for hypertension in Trading Village, Tiris District, Probolinggo Regency.

Efficient and accurate fuel management systems are becoming increasingly important as energy needs and operational complexity increase in various industrial sectors. This study aims to design and implement a fuel flow monitoring and control system using a variable control valve. This system allows real-time monitoring of the level and flow of fuel in the service tank on the ship, as well as automated control. In its implementation, ultrasonic sensors, control valves are combined with LM2596 connected to Arduino nano for data collection, analysis and visualization. The test results show that this system is able to provide accurate data on the flow and level of fuel in the service tank on the ship by displaying the measurement results on the LCD and providing warnings via a buzzer. The LCD display shows the reading of the fuel level and valve opening in the tank. At a fuel level of 0 - 25% the valve will open 100% and requires an average filling time of 25 seconds, At a fuel level of 25% - 50% the valve will open 75% and requires an average filling time of 27 seconds, At a fuel level of 50 - 75% the valve will open 50% and requires an average filling time of 30 seconds, At a fuel level of 75 - 99% the valve will open 25% and requires an average filling time of 32 seconds.