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The climate crisis is no longer just a concern for environmental activists, but has evolved into a strategic threat affecting global stability. The climate crisis is now worsening into a serious threat to the sustainability of human life and the existing ecosystems on Earth. In his book, "The Uninhabitable Earth," Arne Naess provides deep insights thru the Deep Ecology approach, which emphasizes the intrinsic value of all forms of life. This study explores the relationship between the environment and cosmology and its impact on human policies and behavior toward nature. By analyzing the interaction between humans and the environment, we show that a paradigm shift toward a holistic understanding can offer sustainable solutions to this climate crisis. The impact of the climate crisis is highly complex and widespread, leading to unstable weather patterns. These unstable weather patterns threaten agriculture, food security, and also result in more frequent and severe natural disasters. We need to explore the root causes of the current climate crisis, the impacts that have already occurred and may come, and the efforts that can be made by individuals, communities, and the international community to address such challenges. This research strongly highlights the importance of collective consciousness and moral responsibility in protecting the planet, while also inviting readers to reflect on their position within the broader web of life. Thru this approach, it is hoped that synergy between human development and environmental sustainability can be achieved.

This study aims to analyze the interfaith solidarity of UINSU Law students after natural disasters in North Sumatra and Aceh and to identify the forms of social activities and humanitarian values developed through these humanitarian actions. The research method used is a qualitative method with a field research approach through observation, interviews, and documentation. The research data sources were obtained from students, social volunteers, and disaster-affected communities involved in humanitarian activities. The results of the study indicate that UINSU Law students have an important role in helping communities through fundraising activities, humanitarian volunteers, psychosocial assistance, and interfaith cooperation. The interfaith solidarity carried out by the students was able to strengthen social relationships, increase tolerance, and create social harmony in post-disaster communities. In addition, the values of religious moderation, social concern, and unity became the main foundations of the students’ humanitarian activities. The presence of students among disaster victims gave a positive impact on the social recovery process and strengthened the sense of brotherhood and humanity within Indonesia’s multicultural society.

Hand measurements are known to provide a good estimate of a person's height, which is particularly useful in the process of identifying human remains that are dismembered or separated due to various circumstances. Such conditions often occur during mass disasters, murders, airplane crashes, train collisions, and highway accidents. In forensic anthropology, hand length is one of the body measurements that can help estimate height when complete body parts are not available. This study aims to examine the relationship between hand length and height specifically in individuals from the Jambi Malay tribe, one of the ethnic groups in Indonesia. The research design used is analytic with a cross-sectional approach. The type of data used is primary data, obtained directly from 56 respondents belonging to the Jambi Malay tribe, both male and female. Statistical analysis showed that all independent variables — the length of the right and left hands, both in men and women, as well as without gender distinction — had a significant relationship with height. This is indicated by a P-value < 0.05 (P = 0.001). These results suggest that hand length can be a reliable predictor of height in this ethnic group. The study also highlights the importance of conducting further research involving other body parts and ethnic groups to support broader forensic identification efforts.

Earthquakes are natural disasters that frequently occur in coastal areas, posing significant threats to the survival and well-being of local communities. Due to the high vulnerability of these regions, it is crucial for the population to possess adequate preparedness and a strong sense of self-efficacy in responding to such disasters. Self-efficacy, referring to an individual's belief in their ability to overcome challenges or manage difficult situations, is considered a key factor in preparing for and responding to earthquakes. Previous studies have shown that individuals with higher levels of self-efficacy are more likely to be better prepared for natural disasters, including earthquakes. This study aims to examine the relationship between self-efficacy and earthquake preparedness in the Parangtritis community, specifically in Dusun Sono. The primary objective of this research is to analyze the extent to which self-efficacy is related to earthquake preparedness. This study employs a descriptive correlational approach with a cross-sectional design, allowing the researcher to identify the relationship between two variables at a single point in time. A sample of 85 respondents was selected using purposive sampling, based on specific characteristics relevant to the research objectives. The respondents were from the Dusun Sono community, Parangtritis. Data were analyzed using Kendall’s Tau test to examine the relationship between self-efficacy and preparedness for earthquake disasters. The analysis revealed that 74.1% of respondents exhibited high self-efficacy, and 49.9% demonstrated good preparedness. Statistical analysis indicated a significant relationship between self-efficacy and earthquake preparedness, with a p-value of 0.000 (p<0.05), suggesting that the results are highly unlikely to have occurred by chance. Additionally, the correlation coefficient of 0.615 indicates a moderate strength of the relationship between the two variables. These findings provide strong evidence that higher levels of self-efficacy are associated with better preparedness for earthquake disasters.

Floods are one of the most common natural disasters and have a significant impact on the social, economic, and environmental aspects of society. This is particularly evident in the community of East Sorong District. East Sorong District is one of the areas frequently affected by floods, and this inevitably leads to numerous risks and consequences. There are several causes of flooding in the Sorong Timur District, including extreme rainfall, inadequate drainage systems due to trash blockages, uncontrolled land use changes resulting in overpopulation, and the loss of forest areas or green spaces that could function as water absorption zones. Additionally, the lack of flood control systems and weak oversight of development in flood-prone areas can exacerbate flood disaster risks. This study aims to analyze and measure the resilience of the Sorong Timur District in facing flood disasters through an evaluation approach focusing on infrastructure, service facilities, socio-economic factors, community capacity and preparedness, and institutional aspects. It was concluded that the infrastructure variable is still moderate, while the socio-economic variable, basic capacity, and community preparedness, as well as institutional capacity, are still low. Meanwhile, service facilities are also low. Overall, it can be concluded that the resilience of the Sorong Timur district in facing hydrometeorological disasters is weak.

Indonesia is prone to natural disasters because it is located at the confluence of three active tectonic plates. This condition causes high earthquake, volcano, and tsunami activity in Indonesia. Mount Kelud is the most active volcano in Indonesia with cycles that recur every 8 to 15 years. The community service method carried out is to collect data on the area, population, targets, capacity, vulnerability level, and empirical data on the 2014 eruption of Mount Kelud. Then conduct analysis, calculate estimates of health logistics needs, especially reproductive health, socialize the results of the analysis, and conduct disaster preparedness education. This activity was carried out for 6 weeks from March 12 to April 21, 2025. Based on the results of the risk assessment, the Ngancar District, Kediri Regency area has a score of frequent risk scale, severe impact scale, and priority and impact scale in the high category. To overcome the health crisis, a contingency plan is needed, especially for the reproductive health sub-cluster, which includes the preparedness of target data, existing capacity in the region, the level of vulnerability, and the estimated amount of health logistics needed to anticipate the eruption of Mount Kelud. Mount Kelud has a periodic eruption pattern in 8 to 15 years. The contingency plan for dealing with the health crisis of the eruption of Mount Kelud is very important for health service stakeholders because it can minimize the adverse impacts caused, increase rapid response, and ensure smooth coordination between related institutions in dealing with the natural disaster effectively and efficiently. It also supports disaster risk reduction efforts at the community level and strengthens the resilience of local communities.

Currently, the world is facing Global Warning Phenomena, El Nino and La Nina, each of these natural phenomena makes above-average rainfall at a time and place and an area, especially impacting large cities that are passed through by water due to high rainfall. With inadequate city channels to accommodate rainwater flow, it results in, among other things, high floods, landslides due to the soil no longer being able to accommodate high rainfall, high Rob floods due to seawater overflowing into coastal areas of the city. Based on the disaster data due to high rainfall, Research, Handling and Mitigation Planning is needed with the aim of obtaining data for drainage design. The study is the observation of rainfall for 2 years, 5 years, 10 years, and 20 years, so that by calculating the intensity of rain using the Gumbel and Pearson III Log distribution methods, accurate data is obtained to determine the drainage dimensions that must be made in a city and the dimensions of retaining walls along the coast to overcome storm disasters in coastal areas or big cities.

Illegal logging is one of the leading causes of environmental degradation, triggering natural disasters such as floods, landslides, and droughts. Children of Generation Alpha, who are still in the cognitive development stage, are considered vulnerable due to their limited understanding and preparedness for such disasters. This community service program aimed to enhance elementary school students’ awareness and knowledge of disaster mitigation through educational media in the form of printed comics. The activity was conducted by the KKN Team of Universitas Ivet Semarang at SDN Plalangan 02, involving 24 students from grades 3 and 4. The procedure consisted of preliminary observation to assess school needs, comic development on the theme of illegal logging-related disaster mitigation, delivery of the material through comic reading sessions, interactive discussions, and evaluation through pretest and posttest. The pretest results showed that most students were in the "moderate" knowledge category (45.8%). After the intervention, 75% of students reached the "good" category. The Wilcoxon test yielded a significance value of p = 0.001 (p < 0.05), indicating a statistically significant difference in students’ knowledge before and after the intervention. Printed comics proved effective in conveying complex disaster mitigation content in a visually engaging and narrative-driven format. The approach aligns with the characteristics of Generation Alpha, who are highly responsive to visual media. It is recommended that printed comics be further developed and integrated into disaster education programs in elementary schools, especially those located in disaster prone areas.

The policy of mandatory relocation in post-disaster areas, particularly in Cianjur's red zones, plays a crucial role in mitigating risks associated with earthquakes and other natural disasters. This study analyzes the implementation of this policy from the perspective of local government tasks and functions, focusing on the coordination of various stakeholders, legal frameworks, and community involvement. The research uses a qualitative approach, combining legal-normative and sociological perspectives to explore the challenges and conflicts faced during the relocation process. Findings indicate that while the policy has been crucial in safeguarding public safety, its implementation has faced significant challenges such as budget constraints, community resistance, and logistical issues. The study highlights the importance of improving collaboration among local authorities, security agencies, and affected communities. The findings also suggest the need for a more transparent and inclusive approach to policy implementation, ensuring the protection of displaced populations' rights.

Flooding is one of the natural disasters that can occur in various parts of the world and may arise suddenly. However, flood events can be predicted or anticipated through relevant scientific approaches. One such method is by estimating the flood discharge in a given area. Rainfall data is one of the essential inputs required to determine flood discharge. In practice, however, ground-based rainfall measurements often have limitations. To overcome these shortcomings, satellite-based rainfall data can be utilized. There are notable differences between directly measured rainfall data and satellite-derived rainfall data; therefore, satellite data must be calibrated or validated prior to conducting further analysis. One of the most widely used satellite rainfall datasets is the GPM (Global Precipitation Measurement) satellite data, which has a spatial resolution of 0.1° x 0.1°. This study employs a combination of two statistical methods—validation and calibration—to evaluate rainfall data. Prior to evaluation, the RMSE and NSE values did not meet acceptable standards, and the correlation value was low. However, after the evaluation using both methods, improvements were observed: RMSE and NSE values became acceptable, and the correlation increased. These results indicate that the applied methods are effective for evaluating rainfall data. For future research, monthly or annual rainfall data can be utilized to further explore the relationship between different temporal scales of rainfall observations.

Rainfall potential analysis plays a critical role in the management of air resources, mitigation of hydrometeorological disasters, and agricultural activity planning. Accurate estimation of rainfall patterns is essential to ensure effective decision-making in irrigation systems, water resource management, and disaster risk reduction strategies. This study aims to model the probability of rainfall occurrence using a statistical approach based on historical data obtained from the Bureau of Meteorology. The data spans a multi-year period and captures seasonal and regional variability in rainfall events. To characterize rainfall patterns, various probability distributions are tested, including the exponential distribution and the Weibull distribution, which are commonly applied in hydrological studies. Furthermore, the Markov chain method is employed to assess the likelihood of rainfall occurrence on a given day based on the conditions of the preceding day, thereby capturing temporal dependencies. Parameter estimation is conducted using Maximum Likelihood Estimation (MLE), a robust statistical method that enhances the precision of the model. The suitability of each probability distribution in representing the observed rainfall data is evaluated through goodness-of-fit tests such as the Kolmogorov-Smirnov test. The findings reveal that certain distributions align more closely with the local rainfall characteristics, demonstrating the importance of regional analysis in climate modeling. The combination of probabilistic modeling, Markov analysis, and rigorous statistical testing provides a reliable framework for forecasting rainfall. These results are expected to serve as a scientific basis for stakeholders in agriculture, environmental planning, and disaster preparedness, offering insights that support sustainable water resource utilization and risk management.