Journal of Hunan University Natural Sciences

This study presents an innovative strategy for the use of environmental planning tools in protected areas in the context of updating land use plans in Colombia. The problem addressed is the inappropriate use of land that generates socio-environmental conflicts, threatens the integrity and exerts pressure on the main ecosystem of the Moor of the Duende National Park. The objective was to generate a zoning of appropriate land uses under a sustainability premise, integrating environmental determinants and national regulations, such as Law 2372 of 2010 and Decree 3600 of 2007. The methodology included Geographic Information Systems (GIS) analysis, geohistorical compilation of the region, social cartography, and data triangulation. Maps were generated by superimposing cartographic layers and evaluating variables such as erosion, current and potential land use, main ecological structure and use conflicts. Community participation was key to identifying local perceptions and promoting participatory governance. The results identified three levels of conflict (low, medium and high), highlighting critical areas with severe erosion and soil loss in the buffer zone. High-conflict areas were designated for ecological restoration, while low-impact areas were classified for sustainable uses, such as agroforestry and reforestation with native species. In conclusion, the proposed zoning balances ecological conservation and rural development, contributing to the updating of environmental planning instruments. This approach can be replicated in other protected areas, as it combines science, regulations and community participation to resolve land use conflicts, promoting a comprehensive sustainability model.

Keywords: environmental zoning, land use planning, main ecological structure, environmental planning, community participation, environmental governance, protected areas, social cartography, geographic information systems.

https://doi.org/10.55463/issn.1674-2974.52.1.18

This study examines the role of Sanggar Permadani in mediating intergenerational conflicts and fostering cooperation within Javanese families, addressing the challenges posed by modernization. Younger family members often clash with the traditional values upheld by elders, threatening familial cohesion and cultural heritage. Using qualitative methods, including interviews, the research explores how participatory cultural practices, such as pambiwara training, foster dialog and shared learning. The findings reveal that Sanggar Permadani facilitates conflict resolution by creating structured spaces for experiential learning. Younger participants developed an appreciation for traditions, while older members adapted mentorship approaches to connect meaningfully with the youth. These dynamics align with family sociology concepts, including role socialization and interdependence, showcasing the Sanggar’s role in preserving cultural identity and enhancing familial cohesion. This study highlights Sanggar Permadani as a model for transforming familial conflicts into cooperative opportunities, contributing to family sociology and intergenerational cultural preservation practices. This study presents the innovative role of Sanggar Permadani in converting intergenerational tensions into collaborative opportunities through organized, participatory cultural practices. It provides a distinctive framework for safeguarding cultural heritage and promoting familial unity amid modernity by reconciling traditional and contemporary values.

Keywords: education, family, Sanggar.

https://doi.org/10.55463/issn.1674-2974.52.1.17

The problem of chemistry learning that often occurs is the discussion of macroscopic, submacroscopic, and symbolic materials, which is considered difficult by students. Therefore, collaboration skills are needed to make it easier for students to understand chemistry materials. The current learning model is mostly designed to encourage students' collaboration skills. The solution to this problem is to design a learning model that encourages student collaboration, namely, the REAKSI learning model based on the STEM approach. REAKSI represents Research Formulation (R), exploration (E), analysis (A), classification (K), synthesis (S), and implementation (I). This study aimed to implement a new learning model called the REAKSI learning model to improve students' collaboration skills. The novelty of this research is a new learning model that can be used as an innovation in 21st century learning, which is quantitative research using the lesson study method. The samples used were chemistry education students at the University of Riau, Sultan Syarif Kasim State Islamic University, and Riau Islamic University, who were selected using purposive sampling. Data were collected through observations using a Likert-scale questionnaire. Data analysis: The REAKSI learning model based on the STEM approach is more effective in developing collaboration skills from 77% to 90% with a high category. This effectiveness is obtained because the REAKSI learning model includes steps that direct students to engage in collaborative learning activities.

Keywords: Collaboration, Effectiveness, Learning Model, REAKSI.

https://doi.org/10.55463/issn.1674-2974.52.1.16

Dengue fever is a significant public health issue, particularly in tropical and subtropical regions. Tuluá, a city located in the central region of Valle del Cauca in southwestern Colombia, is historically endemic and possesses ideal conditions for the proliferation of the vector. During the first half of 2024, the city experienced an unprecedented outbreak. Despite local efforts, gaps persist in community knowledge about the factors influencing transmission. This study is pioneering and novel as it evaluates knowledge, attitudes, and practices (KAP) and relates them to dengue in the region, integrating geographic information systems (GIS) and spatial analysis of cases and associated variables, which enables the design of targeted and efficient public health interventions. The objective was to determine the KAP of residents regarding dengue and the incidence of cases during the first half of 2024. A descriptive cross-sectional study was conducted, encompassing 401 KAP surveys, household verifications, and reported cases. Data were analyzed using SPSS and QGIS through tables and heat maps to identify spatial and statistical patterns. The results showed that 39.94% of the respondents recognized dengue symptoms, and 87.5% understood its mode of transmission. However, only 35.1% correctly identified the vector breeding sites. Preventive attitudes were limited (12.9% positive), and practices were inadequate: 46.6% of households had breeding sites, and only 12% adequately cleaned water tanks. Heat maps revealed critical areas where breeding sites, larvae, and confirmed cases overlapped, with high-density clusters separated by 10 to 20 m. The findings highlight significant gaps in KAP, which contribute to the persistence of dengue. Strengthening prevention and control measures, epidemiological surveillance, and promoting preventive practices are essential. The integration of KAP with georeferencing provides a replicable model for future research on dengue and other arboviral diseases transmitted by vectors, as it allows for targeted interventions in critical areas and optimizes public health planning in vulnerable urban communities.

Keywords: Dengue, knowledge, attitudes, practices, georeferencing, health, medicine, public health.

https://doi.org/10.55463/issn.1674-2974.52.1.15

Tuberculosis (TB) is a disease caused by infection with the bacterium Mycobacterium tuberculosis in the lungs. TB is a major global health problem, ranking as the second leading cause of death from infectious diseases worldwide. Given that TB is one of the infectious diseases that remains a public health problem, early and accurate detection is key in controlling its spread. This study uses historical data of TB patients from several hospitals in Central Sulawesi as research samples. One of the classification methods is the Support Vector Machine (SVM) method. This method was chosen because of its ability to classify non-linear data and its potential to produce high prediction accuracy with complex data. This study aims to improve the accuracy and efficiency of Tuberculosis (TB) disease diagnosis in Central Sulawesi Province through the application of the SVM method. The parameters used in this study were age, gender, body temperature, shortness of breath, chest pain, sputum examination, and final diagnosis. The results of this study show that handling the problem of imbalanced data with an approach at the data level using the Adaptive Synthetic Sampling (adasyn) method approach and SVM as a classification method for two classes in this study shows that this method can classify each research data used with an accuracy rate of more than 95%. The classification results show that the larger the data used for testing, the greater the classification accuracy. The best classification accuracy value is obtained from the scheme 4 division of training and testing data, namely 90%:10% with a value of 100%. This shows that the method used in this study can be used to help diagnose TB disease based on a patient's medical data. From this research, we introduce a web-based information system that can be used to conduct early detection for TB patients independently, where they are unwilling or embarrassed to come to the hospital.

Keywords: TB disease, Classification, Support Vector Machine, accuracy, Web-based application information system.

https://doi.org/10.55463/issn.1674-2974.52.1.14