The increasing impact of climate change, including rising average temperatures and altered precipitation patterns, has led to changes in the prevalence and distribution of climate-sensitive diseases (CSDs), such as Dengue Hemorrhagic Fever (DHF). DHF remains a significant public health concern in Indonesia, particularly in Banda Aceh, due to its high incidence. The burden on healthcare systems is substantial, contributing to increased morbidity and mortality, especially among vulnerable populations. This study aimed to integrate climate data with machine learning methods to develop predictive models for DHF incidence. Data from 2010 to 2023 included DHF case counts and monthly climate variables such as humidity, rainfall, temperature, and wind speed. The predictive models employed Gradient Boosting, Support Vector Regression (SVR), Random Forest, and Linear Regression algorithms. Model performance was evaluated by comparing prediction accuracy using Mean Absolute Error (MAE) and Root Mean Square Error (RMSE) metrics. The results demonstrated that the Linear Regression model predicted monthly DHF incidence with greater accuracy than the other models, as indicated by lower MAE and RMSE values. These findings suggest that integrating climate data with machine learning provides an effective tool for early warning systems for DHF, supporting public health planning and interventions in Banda Aceh City, particularly in anticipation of an increase in DHF cases.

Disaster management has evolved from a reactive model of post-event relief to a proactive, multifaceted discipline that integrates risk reduction, preparedness, response, and recovery.This paper provides an exhaustive examination of this evolution-from the early days when governments responded ad hoc to catastrophic events, to the development of coordinated national and global frameworks aimed at mitigating disaster impact.The domain of disaster management, which subsumes emergency management and risk reduction, is investigated through the lens of how researchers and practitioners conceptualize the field, the evolution of its measurement systems, and the development of theoretical models.In reviewing over a century of research literature, we explore historical turning points, such as the establishment of civil defence, the post-World War II era of reconstruction and preparedness, and the paradigm shifts associated with the Yokohama, Hyogo, and Sendai frameworks.We further discuss notable models-including the four-phase disaster cycle, structural

The 2004 tsunami, which affected 12 countries, including Indonesia, became a key lesson for urban disaster risk management. Mitigation is now a top priority to protect residents and assets, as well as boost capacity. This study identifies tsunami mitigation strategies in urban areas by categorizing them into small, medium, and large/metropolitan cities. A systematic literature review was conducted using Scopus, Web of Science, SpringerLink, and Google Scholar from 2014 to 2024, applying the PRISMA protocol. Fifty-six articles informed mitigation models for different city sizes. Results show strategies differ by city scale: small cities use community and ecosystem approaches, medium-sized cities adopt intermediate technologies and spatial policies, while large cities focus on advanced technologies and systemic planning. Four main themes emerged: spatial planning, community capacity, early warning and evacuation systems, and integration of technology and science. This study provides both conceptual and practical guidance for mitigating urban disaster risk.

Since community-based disaster volunteers are the backbone of effective disaster preparedness programs, their helpful behavior is crucial in disaster-prone areas. The delivery of psychosocial support will be streamlined if volunteers' helpful conduct is understood. The purpose of this study is to determine the acceptability of the suggested volunteer helpful behavior model. Altruism and egoism-helping behavior are the study's endogenous variables. Social and personal norms, the degree of dependence, and the length of time spent volunteering are the exogenous variables. To address the research questions, a survey-based quantitative study was carried out. 292 community-based volunteers in the Yogyakarta Special Region Province, ages 20 to 61, participated in the survey. Covariance-based structural equation modeling (CB-SEM) was employed for data analysis. Maximum Likelihood Robust (MLR) is the estimate that is employed to overcome anomalous data. The model fits the data, according to the model accuracy index. The analysis's findings indicate that altruism helping behavior is influenced by personal norms and dependency level, and egoism helping behavior is influenced by social norms and dependency level. Implications of the study results: Building volunteer capacity must focus on enhancing society values, personal values, and circumstances enabling help such as standardized physical equipment, knowledge, and abilities.

The continuous evidence of climate change highlights the fact that it is a critical worldwide issue with potentially disastrous consequences for agricultural systems and the livelihoods of socioeconomically disadvantaged societies. This research explores dairy producers’ perceptions of temperature and precipitation changes, their adaptation strategies, and the influencing factors behind these strategies. Data on dairy producers' perceptions was collected by means of a household survey and analyzed utilizing descriptive statistics and graphical representations. Climate data for the study area (1985–2014) was sourced from the Uganda National Meteorological Authority. It was then analyzed using trend analysis. Results from trend analysis were then used to compare with dairy farmers’ responses. Notably, the results show significant agreement between dairy farmers' perceptions and empirical climate data, indicating a clear understanding of climate dynamics. This understanding informs their adaptation practices, which have proven to be diverse and context dependent. These practices include the creation of animal pastures, reforestation, reducing the size of herds through sales, utilizing drought-resistant breeds, and purchasing feed additives for livestock. In addition, the study found that access to credit, household size, education level, and gender are important factors affecting pastoralists' adaptability. These results underscore the importance of recognizing and leveraging farmers' experiential knowledge when developing targeted climate adaptation strategies for specific localities. By bridging the gap between perception and reality, this research provides valuable insights for policymakers for developing tailored climate adaptation strategies and improving resilience within dairy-producing communities in response to climate change

The children with intellectual disability (ID) are vulnerable to Natural Disasters and need priority protection. This leads to the effective implementation of disaster risk reduction (DRR) through integration in school textbooks (ST) as the primary source of teaching and learning, to provide information to ID children. A significant gap is also observed in understanding the extent and adequacy of Natural Disasters in relevant textbooks, accompanied by the potential analysis of appropriate materials. Therefore, this study aimed to examine the inclusion of Natural Disasters in textbooks implemented for ID primary schools using a qualitative content analysis method. All 2020-2021 academic year books were also effectively and efficiently reviewed in presenting the materials of disasters. Results: Six of the 36 textbooks implemented contained natural and integrated materials with thematic titles, namely disasters, seasons, water, land, and earth. In this context, two main themes were identified, including (1) Natural Disasters, namely Hydrology, Geophysics, and Climatology prioritizing floods, landslides/volcanoes, and drought, respectively, and (2) Management Cycle focusing on several stages, such as mitigation, preparedness, and response. Conclusion: The Natural Disasters were experimentally identified, accompanied by integrating the management cycle into school textbooks for students with ID at SPS 1 Padang. This result explained that ID children learned lessons while preparing to encounter Natural Disasters, with preparedness institutionally considered through teachers active participation.

This study aimed to explore emergency planning requirements for managing disasters in the Kingdom of Saudi Arabia (KSA). The study adopted interpretivism; an inductive approach; a descriptive survey; and qualitative methods to address its aim. The techniques used included a literature review and semi-structured interviews. The study sample consisted of 13 experts from the KSA General Directorate of Civil Defense (GDCD). The data were analyzed by using content analysis. The study findings revealed that the emergency planning requirements are administrative requirements, including regulations and legislation; technical requirements, which include equipment; human resources, including staff and responders; identifying, analyzing, and evaluating risks; determining the tasks and responsibilities of the relevant agencies and stakeholders; qualified leadership; determining the chain of command at national and local levels; coordination and cooperation among stakeholders; knowledge gained from local or international experiences; updated database; the availability of sufficient financial resources; completed infrastructure; and improved training and practice. The study also found that although emergency planning requirements are more or less in place, there is a need for further improvement and development; specifically, there is a need for better understanding, knowledge, and awareness. Consequently, it strongly recommends that all emergency planning requirements developed from this study should be implemented simultaneously and as an integrated whole. By doing so, it could help decision-makers and emergency planners at government emergency agencies to improve, develop, and reinforce emergency planning, specifically in reducing disaster risks.

For over two decades (1998, 2008, 2019), floods have occurred in Samarinda in various intensities and different areas. In Bengkuring, flooding has submerged houses for days since 2008. It happens for days with an average depth of 0.5-1 meter. Flooding can cause minor, moderate, and severe damage or destruction of homes, property, and community disorders. People whose homes are submerged by floods make some adaptations to mitigate. Some modifications are to create a small barrier in front of the house, raise the floor, and repair waterways. Safe space is crucial during floods, especially in a one-story house. This study aims to improve the form of adaptation in residential homes in flood-prone areas. Similarly, the objective is to modify the interior to create a safe space for goods and occupants. The method of data analysis is based on Space Syntax Analysis J-Graphs. Occasionally, J-Graphs can efficiently explain interior modifications, including the ratio and layer of safe spaces, the number of indoor and outdoor connecting rooms, and the ring configuration. Through the design approach and prototype demonstration, it is possible to install interior modifications by making mezzanine floors and utilizing the attic. Although most previous research on building adaptation focused on home construction, home interior modification promises advantages that will result in a more straightforward and workable project for the community's needs.

The eruption of Mount Semeru on December 4, 2021, caused a fairly high death toll of up to 50 people. The high number of fatalities is caused by the lack of mitigation capacity and the absence of community involvement in mitigation efforts. Increased mitigation capacity can be done by presenting disaster education to the communities. Thus, we applied the concepts of school watching and town watching in Pronojiwo District, Lumajang Regency. School watching was implemented in eight schools located at Sidomulyo Village. We also carried out town watching in Sidomulyo Village and brought out ±33 residents to the Sidomulyo village hall. The implementation of school watching and town watching in Pronojiwo District can increase community involvement in disaster mitigation efforts and public awareness of mitigation efforts.

This qualitative study aimed to undertake a critical examination of the models by thematic analysis to determine their contribution to disaster management. A review and analysis of the literature were used. The models were studied to explore their contribution to disaster management and to identify any significant constraints or challenges which could limit the ability of the models to carry out appropriate disaster risk reduction actions. The study found that such models are indispensable because they simplify and improve disaster management. Additionally, they may support planners, managers, and practitioners in reaching proper decisions, making them valuable and necessary decision-making support tools. The study also found that the four key phases of disaster management – mitigation, preparedness, response, and recovery – constitute the basis of the majority of models. The study also showed that each model has an advantage that distinguishes it from the other models. The findings also confirmed the doubts raised about the limitations and concerns associated with the models. Concerns included future disasters’ unpredictability, the models’ prescriptive nature, and the impact on businesses. The findings also indicated that certain planners, managers, and practitioners had a limited understanding of the use of models in disaster management. As such, they appear to have overlooked the use of models while dealing with disasters. Hence, the study recommends that the models should be employed in all disaster management phases. The study also recommends that the findings are utilized as a basis for further research into the potential use of disaster management models.