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Generation Z, born approximately between 1997 and 2012, grew up in a period characterized by advancements in digital technology, globalization, and unique social pressures. This article explores the dynamics of physical and mental health among Gen Z, focusing on the challenges and opportunities they face. Physically, a sedentary lifestyle driven by reliance on technology and changes in modern dietary patterns has increased the risk of obesity and metabolic disorders. On the other hand, growing awareness of the importance of exercise and healthy living paves the way for improvement. In the context of mental health, Gen Z experiences higher levels of anxiety, depression, and stress compared to previous generations, largely due to academic pressures, social expectations, and intense exposure to social media. However, the stigma surrounding mental health is gradually diminishing, with more individuals seeking professional help. This article also highlights the importance of a holistic approach, including the integration of digital health technologies and community-based programs, in supporting the well-being of this generation. With a deeper understanding, cross-sector efforts can be made to create an environment that better supports the physical and mental health of Gen Z.

One of the important problems addressed by researchers and specialists is the problem of agriculture and agricultural land and how to sustain or address them in the event that they need a certain treatment or work is being done to develop methods and agricultural tools and patterns used, which in turn affects production, and in this research has been working to study the impact of several factors on production and has been selected specific workers agricultural land, which is harvested land and affected land and total land and has Mathematical statistical methods were used in the analysis and the STIPWISE method  of linear regression was used to determine the effect and any variables affecting and not affecting the dependent variable, which is agricultural production, and the results of the paper found that one of the variables does not affect the dependent variable, which is the harvested land variable.

Law is a guideline and rules related to the concept of living in society and will always be in accordance with the conditions of society. Law is a demand to be able to provide justice, meaning that law is always faced with the question of whether law can realize justice. Related to the concept of law, legal politics is interpreted as an activity that determines the pattern and method of forming law, supervising the operation of law, and updating law for the purpose of the State. Therefore, law is a determinant of politics, and is also related to democracy in the sense that political activities are regulated and must be subject to legal rules. Law is viewed from the perspective of das sollen (necessity), viewing that law must be guided by relations between members of society. While those who view it from the perspective of das sein (reality), empiricists see that law is greatly influenced by politics not only in the process of making it, but also in its empirical realities. So that law is influenced by politics and even now legal autonomy in Indonesia is often intervened by politics, not only in terms of its making, but also in its application, both in terms of law enforcement. This study aims to determine the impact of the development of legal politics in the law enforcement system in Indonesia and the existence of legal politics in the law enforcement system in Indonesia. The method used in the study is normative juridical.

This research aims to describe the learning of Mutei Kawe dance movement patterns in extracurricular activities at SMP Negeri 2 Tebing Tinggi. This research uses qualitative research methods which can be interpreted as philosophical research methods used to study certain populations or samples, collect data using research instruments and analyze qualitative/statistical data. The results of the research show that 1). The teacher's preparation before carrying out extracurricular activities was very good, before learning started the teacher instructed students to immediately change into practical clothes and form neat and orderly lines. 2). The learning process for extracurricular dance activities at SMP Negeri 2 Tebing Tinggi is in the good category. Learning is carried out in 3 stages of activities, namely learning the initial movements, core movements and final movements and students are able to dance the Mutei Kawe dance. 3). And the extracurricular evaluation of the Mutei Kawe dance art used is a practical test by practicing the Mutei Kawe dance in groups in the form of individual assessments. month, namely 4-5x meetings.

The coastal area in Aeng Batu-Batu Village, Galesong, Takalar Regency is one of the areas whose lives depend on marine products, especially on seaweed cultivation as their main livelihood. However, due to the sea mining activities that began in the area since 2017 to meet the needs of infrastructure projects on the Center Point of Indonesia (CPI) reclamation island, it has had a significant impact on the social life of the local community, a change in income that has decreased from seaweed cultivation which has finally made fishermen switch to looking for other marine biota such as crabs and squid. In the context of social dynamics that occur as a result of mining, it has made changes in the daily activities of the local community, especially in the search for income. In this case, the solidarity of the local community is also an important factor in changing habits that occur after sand mining occurs. Sand mining also triggers coastal abrasion which causes houses in coastal areas to be exposed to abrasion. This research uses qualitative methods that focus on interview techniques, observation and literature review which are used to analyze the effects of sand mining on the coastal communities of Aeng Batu-Batu Village. The results of this study show that coastal sand mining has brought changes to the social dynamics and interaction patterns that exist in the community, especially in the management of marine resources and their place of residence. These results are expected to be material for further attention regarding coastal environmental management policies related to the utilization of natural resources, especially for reclamation needs in order to prevent negative impacts that arise in coastal communities.

This research seeks to identify the sources and locations of arithmetic learning challenges related to integer counting operations. Class VI, which is the focus of this study, has an average math score that is lower than the KKM. Methods such as tests, observations, and interviews are used to gather data. Students' mastery of the topic of whole number counting operations was assessed using the test technique, which consisted of a 10-question essay. Finding out how the subject is doing during math learning activities and what variables could influence math learning are both accomplished via the use of the observation technique. The purpose of the interview was to get a clear understanding of the challenges that students have while studying the content for integer counting operations. Fifty percent of students had trouble with skills, 23.3% had trouble with ideas, and 20% had trouble with problem solving, according to the data from the final analysis. This includes students in the adequate group. Teachers are encouraged to shape mathematics teaching patterns based on more than just pupils' problem-solving abilities. More significant, however, is figuring out how to encourage pupils to comprehend and fully grasp current ideas so that they do not have any trouble understanding mathematics. 

OpenCV is a widely used library in the field of image processing and computer vision. Combined with Python's flexibility, OpenCV provides an extensive range of functions for efficient image processing, modification, analysis, and visualization. This paper aims to introduce the fundamental concepts of image processing using Python and OpenCV, including image reading, color conversion, edge detection, and image manipulation such as resizing and cropping. Furthermore, this study discusses basic analysis techniques like color distribution histograms and feature detection. By presenting these concepts, the paper aspires to help readers understand the foundations of digital image processing and explore the potential applications of OpenCV in practical fields such as pattern recognition, object detection, and image segmentation.

The tourism potential in the Sampang Regency area is very good, one of which is rice tourism in Ataman village. Padi tourism offers beautiful views with typical village culinary attractions. However, in rice tourism there are still problems such as visitors not respecting the cultural values ​​and beliefs of the local community and managers also do not have tourist regulations. Therefore, this results in a decrease in tourist visitors so that the contribution of PADes automatically decreases. The research method used is empirical juridical research with a field study approach. Data collection in this research uses several methods including interviews, observation and literature search. The research location is Taman Village, Jrengik District, Sampang Regency. The data analysis method used in this research is descriptive-qualitative. The results of research during the MBKM KKNT show that the management of Rice Fields Tourism in Taman Village is still not well organized, considering that the management pattern of facilities and infrastructure is still lacking, especially the management does not have rules for tourist visitors, so tourism is quite quiet so that PADes decreases. Therefore, the MBKM KKNT program created a legal education program regarding the protection of tourist visitors within the framework of preventive protection. The results are quite satisfactory from the results of the socialization showing that understanding of village officials, tourism managers, the community and tourist visitors has increased, especially understanding of the substance of the Tourism Law and the Village Law. Apart from that, the management makes rules for issuing visitors based on statutory regulations and the management is improved gradually, so that tourist visitors will gradually increase and the Village Paddy will automatically increase and this will all make the Taman Village community prosperous.

Indonesia is a country with highly diverse flora, ranking second in the world for its megabiodiversity. Araceae is a group of monocotyledonous Angiosperms characterized by flowers arranged in a spadix surrounded by a spathe, with either unisexual or bisexual inflorescences. This study aims to examine the diversity, distribution patterns, and utilization of Araceae species in the Bumi Sahaja Village Forest, using purposive sampling techniques with station placements based on forest types. The research findings show that there are 668 Araceae individuals, divided into 13 species, with moderate diversity and an even distribution pattern. Schismatoglottis calyptrata has the highest importance value, which is 47.14. In conclusion, 13 species of Araceae have been identified, with moderate diversity at each station, even distribution patterns, and two Araceae species used as ornamental plants, namely Alocasia lauterbachiana and Monstera adansonii.

Artificial Intelligence (AI)plays a vital role in criminal investigations, offering innovative solutions to challenges faced by law enforcement. With its fast and accurate data analysis capabilities, AI can identify behavioral patterns, detect anomalies, and predict potential crimes. Technologies such as facial recognition, social network analysis, and natural language processing help speed up the investigation process and improve prosecution effectiveness. However, the application of AI also raises ethical challenges, including privacy issues and potential bias in algorithms. Therefore, it is important to develop a framework that ensures the responsible use of AI in a legal context.    

The Water Quality Index (WQI) shows the condition of water quality in an area based on the status of water quality resulting from the measurement of physical, chemical and bacteriological parameters of a water body both rivers and lakes. Several machine learning techniques can be used to predict water quality in an area, one of which is through the prophet model approach which is able to provide fairly accurate predictions for the water quality index in Indonesia. The main objective of this research is to obtain a WQI prediction value as a baseline in the formulation of future environmental control activity policies using the prophet model. The result is that the predicted value of IKA for 2021-2023 generated through machine learning with the prophet model approach shows that the Mean Absolute Error (MAE) value: 7.01, Root Mean Square Error (RMSE): 8.61 and Mean Absolute Percentage Error (MAPE): 13.06%, which means that IKA prediction with the prophet model is effective in capturing annual patterns between historical data and future predictions.    

This study presents an advanced approach to multi-class skin lesion classification by leveraging an ensemble model comprising the Inception-V3, ResNet-50, and VGG16 architectures. The classification task focuses on categorizing skin lesions into distinct classes, including Melanoma, basal cell carcinoma (BCC), and squamous cell carcinoma (SCC), using the ISIC dataset, a comprehensive collection of dermoscopic images. In order to properly balance the dataset, the oversampling strategy is utilized, as some lesion types are underrepresented due to inherent imbalances in the dataset. By ensuring that the model is trained on a more representative dataset, this balancing improves the algorithm's capacity to categorize all lesion types properly and impartially. By combining the complementary features of ResNet-50, Inception-V3, and VGG16, the ensemble technique improves the overall classification performance. ResNet-50 is chosen for its deep feature extraction capabilities, which help capture fine details in lesion patterns. Inception-V3 is selected for its multi-scale processing, allowing it to effectively analyze lesions at varying resolutions and sizes. VGG16 is included due to its simple yet highly effective architecture for image classification tasks. The ensemble model with data augmentation significantly outperforms individual models in skin lesion classification for both the original and balanced ISIC datasets regarding accuracy, precision, recall, and F1-score. This method offers a robust solution for skin lesion classification, contributing to more accurate and reliable diagnostic tools in dermatology.

Dangeu dengue fever or what we often call dengue fever is a disease transmitted by the Aedes aegypti mosquito and caused by the dengue virus. This disease can potentially cause serious complications if it does not receive proper treatment. In this research, the author uses the application of artificial neural networks with the Hebb rule approach to predict the risk level of dengue fever. Predictions are made based on factors such as weather conditions, population density and historical case data that influence this disease. The Hebb rule is used in this research because of its ability to strengthen connections between neurons based on the input patterns they receive, so it is hoped that it can produce more accurate predictions. Test results show that this method has a fairly high level of accuracy in predicting the pattern of dengue fever cases in an area. This research indicates that the application of artificial neural networks with the Hebb rule can be an effective tool for related parties in taking preventive measures to minimize the number of dengue cases in the future.    

This study shows that team collaboration dynamics greatly affect work quality and goal achievement. These dynamics include various elements, including communication, coordination, interdependence, and trust among team members. The methodology of this study aims to provide detailed insights into team collaboration dynamics and work efficiency, with a focus on organizational success in achieving organizational goals. The interpersonal communication patterns of managers that were found and had a significant impact on Caffe Otsukohi team performance were democratic communication patterns and laissez-faire communication patterns. Supporting factors for interpersonal communication between managers and Caffe Otsukohi employees include transformational leadership, a positive work environment, effective communication channels, and shared goals.

KPRI KOKARNABA Baturraden faces challenges in managing increasingly complex sales data, particularly in identifying the most in-demand products to maximize profit. This study aims to analyze sales patterns using the Naïve Bayes algorithm as a probability-based classification method. The collected sales data were analyzed to identify categories of best-selling and less popular products within the cooperative. The results indicate that the Naïve Bayes algorithm has an accuracy rate of 77.56% in predicting product categories. This research is expected to assist the cooperative in optimizing stock management and improving member satisfaction.

This study aims to describe and analyze the Choreography of the Galuak Plate Dance at the Pinang Sinawa Kenagarian Taratak Art Studio, Sutera District, South Pesisir Regency. This type of research is qualitative research using a descriptive method. The research instrument is the researcher himself and is assisted by supporting instruments such as stationery and mobile phones. Data were collected through literature studies, observations, interviews and documentation. The steps of analyzing data are collecting data, describing data and inferring data. The results of the study show that the galuak plate dance has 3 parts, namely the beginning as the opening of the dance, the middle part, and the final part as the climax. In this galuak plate dance, there are elements of dance composition consisting of; movement, floor design, group composition, top design, dancers, music design, costumes and makeup and props. The movements worked on by the choreographer describe the daily life of the Kenagarian Taratatak community. This dance work also looks very interesting with various floor patterns and group compositions so that the audience does not get bored in watching the performance and the various dancers who master soft movements and strong movements. The costumes used in the plate dance are simple costumes. This galuak plate dance raises the theme of the community's gratitude for the harvest. The music that accompanies the dancers' movements uses a tempo that is initially slow and rises to the end with a singing song. The properties used in the galuak plate dance are plates and shells. 

This research investigates the electromagnetic field (EMF) characteristics generated by solar power plants, focusing on their potential environmental and health impacts. The study employs a dual methodology combining direct measurements using gaussmeters and computer simulations using COMSOL software to map electromagnetic fields around solar power installation components. Measurements were taken under two conditions: during solar power plant operation and non-operation, to establish comparative baseline data. The research found significant variations in electromagnetic field intensity based on operational status and distance from components, particularly near inverters and cable networks. Results indicate that EMF levels are higher during operation, with field strength decreasing exponentially with distance from the source. These findings contribute to understanding EMF distribution patterns in solar installations and provide valuable insights for implementing appropriate mitigation strategies to ensure safe operation within established exposure standards.

This research analyzes the consumption behavior patterns of the people of Blitar Regency and City in the context of national food efficiency from an Islamic economic perspective. The aim of the research is to identify people's consumption behavior patterns, the food efficiency strategies implemented, and the obstacles faced in national food efficiency efforts. The research method used is a descriptive qualitative approach with data collection techniques in the form of in-depth interviews, observation and documentation. The research results show that the consumption patterns of Blitar people tend to shift from staple food to non-food as prosperity increases. Food efficiency efforts are carried out through increasing production at low costs and optimizing income. However, there are obstacles in the form of uneven efficiency in the production to consumption chain. This study recommends increasing public awareness to avoid wasting the implementation and concept of maslahah in consumption patterns according to Islamic teachings.

The phenomenon of online loans has increased significantly in Indonesia, presenting its own challenges for the community in terms of financial management. One of the impacts of the rise of online loans is the emergence of an unhealthy debt culture, where many people are trapped in a debt pattern that is difficult to control, leading to default. This study aims to examine the role of financial literacy as an important factor in overcoming the culture of excessive debt and reducing the number of defaults on online loans. The method used in this study is a literature review that focuses on data from other relevant document sources and those that use online loan services. The results of the study show that financial literacy education can provide the community with a better understanding of financial risks and responsibilities, as well as encourage wiser behavior in making financial decisions.

The use of Artificial Neural Networks (JST) for weather prediction is one of the innovative approaches in climate data analysis. This study aims to apply JST in predicting weather, especially rainfall and the number of rainy days in the North Sumatra region. Historical weather data obtained from BMKG Region I for 2022-2023 is used as input to train the JST model. With a training process that involves processing rainfall data, this model is expected to provide accurate predictions regarding weather patterns. The results of this research can help in agricultural sector planning, disaster risk mitigation, and natural resource management. JST has proven to be effective in identifying dynamic and complex weather patterns, so it has the potential to be used in long-term weather prediction.