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Legal protection of children refers to all actions that ensure and safeguard children and their rights so that they can live, grow, develop, and engage maximally in line with human dignity and honour, as well as get protection from violence and discrimination within legal laws. In Indonesia, the proportion ranges from 22 to 100%, indicating that the aforementioned conditions occur often. As a result, researchers are interested in performing this study utilising normative research methodologies. Legal protection for minors who distribute pornographic videos on social media, choosing to release minors, is regulated by Law No. 23 of 2002 concerning Child Protection, Article 16 (1) Every child has the right to receive protection from being the target of abuse, torture, or inhumane punishment, (2) Every child has the right to obtain freedom in accordance with the law, and (3) Arrest, detention, or incarceration of a child must be carried out in accordance with relevant legislation and only as a last option. And advocate LPKA in the form of independence coaching, which includes instruction for foster children in skills that may be developed after the foster time ends, such as sewing. Meanwhile, personality development is moral development, with the goal of providing foster children with an understanding of social norms as well as an understanding of themselves so that they can accept responsibility for all actions they take and refrain from repeating illegal actions. Suggestions in this protection are expected to be safeguarded by anybody, regardless of circumstance, and the local government needs to get to the field to inspect the status of special child development institutions so that any deficiencies may be corrected quickly, allowing development to proceed correctly.

This study investigates the utilization of Artificial Intelligence (AI) to promote ethical business practices within the evolving landscape of digital marketing in Indonesia. The research aims to elucidate the current state of AI integration, its impact on ethical considerations, and the challenges and opportunities it presents. The study adopts a qualitative approach, employing semi-structured interviews and focus group discussions with key stakeholders involved in digital marketing and AI development. Sampling techniques include purposive sampling to ensure representation across industries and snowball sampling to access knowledgeable participants. Data analysis follows thematic analysis principles, identifying recurring patterns, themes, and divergences related to ethical concerns and AI implementation. Preliminary findings indicate a nuanced relationship between AI adoption and ethical dilemmas, with emerging strategies to balance innovation with ethical principles. This study contributes to understanding the ethical implications of AI in digital marketing and offers insights for businesses, policymakers, and scholars aiming to navigate this complex terrain responsibly.

This research aims to explore strategies for maximizing human capital in the context of advancing artificial intelligence (AI) technologies within the workforce. The study employs a phenomenological approach to understand individuals' experiences and perceptions regarding AI integration in the workplace. Through purposive sampling, data were gathered from a diverse pool of professionals across industries. Semi-structured interviews were conducted to delve into participants' perspectives on the impact of AI on job roles, skill requirements, and organizational dynamics. Thematic analysis was employed to identify recurring patterns and emergent themes within the qualitative data. Preliminary findings suggest a nuanced interplay between AI technologies and human capabilities, highlighting the need for upskilling, retraining, and fostering adaptability among employees. The study contributes to the discourse on optimizing human resources amidst rapid technological advancements, offering insights for organizational strategies to harness the synergy between human expertise and AI innovations in the future workforce.      

In the rapidly evolving landscape of artificial intelligence (AI), optimizing human resources (HR) practices is imperative to foster organizational excellence. This qualitative research aims to explore the intersection of AI and HR practices to enhance organizational performance. The research adopts a qualitative approach utilizing in-depth interviews with HR professionals, AI specialists, and organizational leaders. Sampling techniques include purposive and snowball sampling to ensure diverse perspectives are captured. Data analysis involves thematic analysis, allowing for the identification of patterns and themes within the qualitative data. Preliminary findings indicate that organizations are increasingly leveraging AI to streamline HR processes, enhance talent acquisition, and improve employee engagement. Furthermore, the research reveals the significance of ethical considerations and human oversight in AI-driven HR practices. This study contributes to the growing discourse on AI integration in HR and provides insights for organizations aiming to navigate the AI-driven landscape while fostering excellence in HR practices.  

This research aims to explore strategies for cultivating exceptional talent in the era of artificial intelligence (AI). The study employs a mixed-method approach, integrating interviews, surveys, and case studies to gather comprehensive data. The sample selection includes individuals from various industries known for fostering talent development, such as technology, education, and business. Through thematic analysis, the collected data are systematically examined to identify recurring patterns, emerging themes, and innovative practices in talent cultivation. Results reveal multifaceted strategies encompassing personalized learning, mentorship programs, continuous feedback mechanisms, and proactive skill development initiatives. Furthermore, the study highlights the significance of human-centric approaches in leveraging AI technologies to enhance talent development efforts. The findings contribute to a deeper understanding of how organizations can harness human potential effectively amidst technological advancements, paving the way for sustainable talent management practices in the AI era.    

The events of the covid-19 pandemic produce an uncertain future. This has a very far-reaching influence on capitalization of capitalization and also social problems such as increasing levels of violence and crime rates. The purpose of this study is to analyze government policies regarding reactions due to inflation, especially in Indonesia. Inflation rate has a negative effect on the reaction load. The inflation rate affects the response because when the stimulus increases, inflation will decrease and vice versa. There are several government policies in overcoming pressure due to inflation, namely creating jobs, changing the investment climate, spreading several economic stimulus, and improving the quality of human resources through education.    

Unemployed are people or people who have not got a job, are looking for work and have lost their job or are not working at all. This study aims to analyze Government Policy Related to the Threat of Unemployment Post-Inflation Increase in DKI Jakarta. The research method used in this research is by using quantitative methods. The object of analysis will be obtained from BPS or the Central Statistics Agency. BPS is an institution that deals with censuses and statistics. The results show that the numbers can affect a state's income because not having income can cause economic problems and poverty. Therefore, government policies are urgently needed to overcome this unemployment.  

This study aims to analyze the influence of SEA and E-WoM on college decisions for Digital Business Study Program, Universitas Al Irsyad Cilacap, The object of this research is the Digital Business Study Program at Al-Irsyad Cilacap University, while the subjects are students of the Digital Business Study Program at Al-Irsyad University Cilacap. sampling with purposive sampling technique. The number of samples in this study were 31 respondents. Data was obtained through questionnaires which were distributed directly to digital business students at Al-Irsyad University, Cilacap. The data analysis technique uses SPSS version 22. Based on the results of the analysis carried out, it shows that SEA has a positive effect on digital business study study decisions, E-WoM has a positive effect on digital business study study decisions.

Pelvic inflammatory disease is a reproductive system disorder in women that can be caused by viruses or bacteria. Pelvic inflammatory disease is an inflammatory process of the female genital organs in the pelvic cavity, namely the genital tract consisting of the uterus, fallopian tubes and surrounding areas including the peritoneum. It is caused by Neisseria gonorrhoeeae or Chlamidia trachomatis and may be the organism involved in bacterial vaginosis. Objective: This study aims to describe the risk factors for pelvic inflammatory disease experienced by women of childbearing age. Research methods; This study uses an analytical survey. The population in this study were all cases of GSR who were treated in hospitals. Andi Makkasau, Parepare City with a total of 247 people. The sampling technique was purposive sampling. The method of data collection in this study is secondary data, namely if the desired data collection is obtained from other people or other places and is not carried out by the researcher himself where in this study the researcher records the register number of patients with pelvic inflammation (PRP) obtained from the register book at the GSR treatment room or medical record. Then take the patient's status on the medical record at Andi Makkasau Hospital. After that, take the data and select the complete data based on the specified criteria. The data were analyzed using chi-square. namely if the desired data collection is obtained from other people or other places and is not carried out by the himself where in this study the researcher records the register number of patients with pelvic inflammation (PRP) obtained from the register book at GSR treatment room or medical records. Then take the patient's status on the medical record at Andi Makkasau Hospital. After that, take the data and select the complete data based on the specified criteria. The data were analyzed using chi-square. namely if the desired data collection is obtained from other people or other places and is not carried out by the himself where in this study the researcher records the register number of patients with pelvic inflammation (PRP) obtained from the register book at GSR treatment room or medical records. Then take the patient's status on the medical record at Andi Makkasau Hospital. After that, take the data and select the complete data based on the specified criteria. The data were analyzed using chi-square.

Family support is assistance that can be given to other families in the form of goods, services, information, and advice which makes the recipient of support feel loved and appreciated. In this case, family support will bring a sense of joy, security, satisfaction, and comfort that makes pregnant women feel emotionally supported which will affect their mental well-being. Objective: This study aims to determine the relationship between family support and anxiety in Primigravida pregnant women in the third trimester in the work area of  the Simeulue Tengah Health Center UPTD, Simeulue Regency. Method: This research method is an analytical survey with a cross-sectional approach with a sample size of 36 respondents using the total sampling technique. The study began on December 16-20, 2022. Results: Family support is in the sufficient category with 16 respondents (44.4%) and the level of anxiety in Primigravida pregnant women in the third trimester is in the moderate and severe categories, each with 12 respondents (33.3%). Conclusion: Based on the results of the study, it was found that there was a relationship between family support and anxiety levels in Primigravida pregnant women in the third trimester at the UPTD Simeulue Tengah Health Center, Simeulue Regency with a p-value = 0.043. Suggestion: It is hoped that medical personnel at the Health Center can provide counseling to families who have pregnant women.

Emerging technologies play a crucial role in transforming education by fostering inclusivity and equity. This study explores how artificial intelligence, virtual reality, and adaptive learning platforms contribute to overcoming traditional barriers to education. The research adopts a qualitative approach, analyzing case studies and recent advancements in educational technology. Findings reveal that these technologies enhance accessibility for students with disabilities, provide personalized learning experiences, and bridge educational gaps in underprivileged regions. The study highlights the importance of policy support and infrastructure development to maximize the benefits of technological integration in education. The implications suggest that adopting emerging technologies can create a more inclusive and equitable learning environment, ensuring education for all.

The increasing use of social media among students has raised concerns regarding its impact on academic performance and digital well-being. This study aims to examine the relationship between social media usage, student learning outcomes, and overall well-being in a digital environment. Using a mixed-methods approach, data were collected through surveys and in-depth interviews with high school and university students. The findings indicate that while social media can serve as a valuable tool for academic collaboration and resource-sharing, excessive and unregulated usage often leads to distractions, reduced academic performance, and negative effects on mental health. The study highlights the need for balanced social media engagement and the implementation of digital literacy programs to promote responsible usage. These insights contribute to the ongoing discussion on digital well-being and offer practical recommendations for students, educators, and policymakers.  

The integration of Artificial Intelligence (AI) in education presents both challenges and opportunities for 21st-century learning. This study explores the transformative potential of AI in enhancing personalized learning, adaptive assessments, and intelligent tutoring systems. The research aims to identify the key barriers to AI adoption in educational settings, including ethical concerns, data privacy, and technological infrastructure. Utilizing a qualitative approach, data were collected through literature reviews and expert interviews. The findings indicate that while AI can significantly improve learning outcomes and administrative efficiency, its implementation requires strategic planning, teacher training, and regulatory frameworks. This study highlights the importance of balancing AI-driven innovation with ethical considerations to maximize its benefits in education.

This research to analyze the contribution of variables from three economic policies, with monetary policy through interest rate variables, exchange rates, and money supply in facing economic recession. Where the fiscal policy variable is through tax value. Then macroprudential policy through Non Performing Loan and Capital Adequacy Ratio variables. This study uses secondary data or time series, namely from December 2019 to February 2021. The data analysis model in this study is the Vector Autoregression (VAR) model which is seen from being sharpened with Impulse Response Function (IRF) analysis and Forecast Error Variance Decomposition (FEVD), Panel ARDL, and Different Tests. The results of the IRF analysis show that the stability of the response of all variables is formed in period 8 or the medium and long term, where the response of other variables to changes in one variable shows different variations, both from positive responses to negative responses or vice versa, and there are variables whose responses remain positive or remain negative from the short term to the long term. The results of the FEVD analysis show that for the short-term inflation variable it is influenced by inflation itself and in the medium and long term it is influenced by interest rates. For the JUB variable in the short term it is influenced by JUB itself and in the medium and long term it is influenced by NPL. For the interest rate variable in the short term it is influenced by JUB while in the medium and long term it is influenced by the exchange rate itself and CAR. For the tax variable in the short, medium and long term it is influenced by the tax itself and JUB. For the NPL variable in the short, medium and long term it is influenced by JUB and tax. For the CAR variable in the short, medium and long term it is influenced by JUB and tax. Then the results of the ARDL Panel analysis show that the country that is able to become a leading indicator in controlling the economic recession in the Four of The Group Twenty, namely Turkey, is only done by interest rates. While South Africa is done by interest rates, taxes, NPL, and CAR. For Russia, it is done by all variables, namely the amount of money in circulation, interest rates, exchange rates, taxes, NPL, and CAR. Meanwhile, Indonesia is carried out by exchange rates, taxes, NPL and CAR.

This revitalization is carried out by reorganizing the function of space, and cultural values, and strengthening information about cultural heritage, as stated in Law Number 11 of 2010 concerning cultural heritage in article 80 paragraphs (1) and (2). Following the principle of development in general, revitalization must provide benefits to improve the quality of life of the community. This revitalization feasibility study uses primary data and secondary data. The results of the feasibility study on the revitalization of Merdeka Field Medan are the condition of the existing facilities and infrastructure of Merdeka Field, many of which are damaged or no longer functioning. There are even landfills in several corners of the Merdeka Square area. The drainage channels of the area are also not well integrated into the city's drainage system. And based on the problem of existing infrastructure, the Merdeka Square revitalization plan is very feasible to do.    

Smart wearable technologies are becoming essential tools for real-time health monitoring, offering a new dimension of personalized medicine. Wearable devices equipped with biosensors, artificial intelligence, and Internet of Things (IoT) connectivity can continuously track vital signs such as heart rate, blood pressure, oxygen levels, and even detect early symptoms of diseases. This paper explores the latest advancements in wearable health technology, including flexible electronics, energy-efficient data processing, and integration with telemedicine platforms. Additionally, ethical concerns such as data privacy, cybersecurity risks, and user adoption challenges are discussed. The study provides insights into how smart wearables can be effectively utilized for preventive healthcare, chronic disease management, and real-time health diagnostics.

The advancement of Autonomous Underwater Vehicles (AUVs) is transforming the way scientists conduct deep-sea exploration and environmental monitoring. AUVs equipped with sophisticated sonar, AI-driven navigation systems, and real-time data transmission capabilities can explore extreme marine environments where human intervention is impossible. This paper reviews state-of-the-art developments in AUV technology, including enhanced battery efficiency, swarm intelligence for coordinated underwater missions, and AI-based anomaly detection for marine biodiversity assessment. Additionally, the study highlights the role of AUVs in disaster response, such as oil spill detection and ocean pollution analysis. By addressing technical challenges such as communication latency, data processing in harsh environments, and energy efficiency, this research aims to contribute to the next generation of AUV applications.

Background : Diarrhea is still the leading cause of morbidity and mortality in the world. According to data from the United Nations Children's Fund (UNICEF) and the World Health Organization (WHO) in 2013 diarrhea is the second leading cause of death in children under five. The purpose of the study was to determine the relationship between mother's education level, occupation, income, mother's knowledge, and latrine ownership with the incidence of diarrhea in children under five in Bram Itam Kiri Village.Methods : Using a cross sectional approach with a population of 166 mothers, the number of samples was 68 respondents. The sampling technique was carried out using simple random sampling. Data were collected using a questionnaire sheet and analyzed univariate and bivariate using chi square analysis.Results : The level of education in the low category is 48.5%, employment in the unemployed category is 58.9%, income in the low category is 70.6%, knowledge in the poor category is 83.8%, latrine ownership in the category does not meet terms of 61.8%. Bivariate results of education level (0.003), mother's occupation (1,000), family income (0.019), knowledge (0.028), and latrine ownership (0.002) with the incidence of diarrhea in children under five.Conclusion : There is a relationship between the level of education, family income, knowledge, and ownership of latrines, and there is no relationship between the mother's occupation and the incidence of diarrhea in children under five.      

One of the stunting locations in East Tanjung Jabung Regency is located in Geragai Sub-district, Pandan Lagan Village. According to data from the Puskesmas in 2019, the incidence of stunting in Pandan Lagan Village was 35 toddlers, in 2020 it was 17 stunting children out of a total of 70 children in Pandan Lagan Village. The purpose of this study was to determine the relationship between maternal nutritional status, history of maternal conditions, and maternal knowledge about 1000 HPK with the incidence of stunting in Pandan Lagan Village. This type of research is quantitative research, using a cross-sectional approach. The number of samples to be studied with the Lemeshow Formula is 45 respondents. The dependent variable is stunting and the independent variables are maternal nutritional status (pre-pregnant maternal BMI and weight gain during pregnancy), history of maternal conditions (maternal age during pregnancy, birth spacing), and maternal knowledge about 1000 HPK. The research instrument used a questionnaire sheet, then the data was processed through data editing, data coding, data entry, data cleaning, and data processing, then analyzed univariate, bivariate with a chi-square test, and multivariate with multiple logistic regression test. Based on the results of the study, there is a relationship between pre-pregnancy maternal BMI with a risk of 4,464 times, weight gain with a risk of 3,75 times, maternal age during pregnancy with a risk of 3,0 times, and spacing of babies with a risk of 2,444 times with the incidence of stunting. There is no relationship between maternal knowledge about 1000 HPK and the incidence of stunting with a p-value = 0,114, and it is known that the pre-pregnancy mother's BMI variable is the variable that has the greatest influence on infants with stunting nutritional status (odds ratio = 15,943). For this reason, it is expected to be more intensive in educating couples of childbearing age, pre-pregnant mothers, or early on to adolescent girls to pay attention to factors that affect stunted children, especially to have an ideal BMI so that it will reduce the risk of having children with stunted nutritional status.    

This study analyzed the writing skills in English expository text. There are five indicators in writing expository text: content, organization, grammar, vocabulary, and mechanics. This study aimed to investigate the students' writing skill on expository text related to the five indicators of English expositorytext and investigated the difficulties in writing English expository text. This research study used a descriptive quantitative research design. The participants were first semester students at English Literature Study Program of Universitas Trunojoyo Madura. The data collected from students' writing expository text test and analyzed by using Heaton’s theory. The result data analysis showed that: 1) 47% of students were average to good in writing content, 2) 51% of students were average to good in writing organization, 3) 31% of students were average to good in using grammar, 4) 36% of students were very good to excellent in using vocabulary, 5) 44% of students were very good to excellent in writing mechanics. This research found some difficulties the students when writing expository text. First, students cannot develop their ideas. Second, students are unable to develop their idea based on topic that they have to explain in expository text. Third, students struggle with grammatical structure of expository text. That means, they have to more understand about the simple present tense. Fourth, they were difficult to select appropriate vocabulary when writing expository text. The last, they miss-spelt words and were unsure of proper punctuation that was causing an error of mechanics.