In Indonesia, natural disasters cases have significantly increased from time to time and have the largest impact on economic losses. To avoid losses in the future due to natural disasters, the insurance company needs to estimate the risk and determine the rate of premium that would be charged to the policyholder. In conjunction with the present issue, this study seeks to determine the premium rate and estimate the size claim of insurance by considering the mitigation fund reserve decisions using The Collective Risk Model (CRM). The data was analyzed using the Poisson process with Weibull distribution to determine the natural disaster frequency and losses. The distribution of losses is estimated using Maximum Likelihood Estimation (MLE), and the magnitude of losses was estimated using the CRM. Also, the mean and variance estimators of the aggregate risk were used to estimate the premium charged. The results indicated that expectation and variance of the frequency of incident claims have the same value, i.e., 2562. Also, the loss claims follow the Weibull distribution with the expected value and variance of 5.81309×10¹⁰ and 2.5301×10²², respectively. The mean and variance of the aggregate (collective) claims are 148,931,365,800,000 and 7.35×10²⁵, respectively. In conclusion, this study has successfully determined the efficient pure premium model through the Standard Deviation Principle (SDP). SDP provides a much cheaper premium than the Expected Value Principle with the same loading factor. In addition, SDP considers the standard deviation of the collective risk of natural disasters. The implications of the results of the premium determination are expected to be the basis for decision-making for insurance companies and the government in determining insurance policies for natural disaster mitigation.

Natural disasters are one of the events that threaten food security in every region in Indonesia. Ciamis District is one of Indonesia's areas prone to natural disasters. One of the impacts of a disaster is on the agricultural sector because it will determine food security in the area and can affect the socio-economic community. This study aims to analyze the Geographically Weighted Regression (GWR) Model of the Effect of Disaster Events on Food Security. This study used quantitative methods, and data sources were obtained through secondary data searches. Data were processed using a Geographically Weighted Regression (GWR) analysis tool through a quantitative descriptive analysis approach. The results showed that the natural disasters directly or indirectly impacted food availability and security in Ciamis District. Natural disasters still occur even though food availability, affordability, and utilization are quite good. There are other factors, namely disasters, that come suddenly and cannot be predicted, thereby affecting the food security of a region. Efforts are needed to create togetherness in society to anticipate and respond to disaster events. In addition, it is expected that each individual can take the necessary actions to solve problems independently.

Climate change and global warming have led to many risks and changes for the Earth, including the increase in natural fires, floods, air pollution, unusual seasons, etc. The increase in the trend of global warming may bring many countries underwater. For instance, the populous Asian nation of Bangladesh is most vulnerable to rising sea levels. It is estimated that a rise of just one meter in sea level is enough to submerge 30,000 square kilometres of the coastal areas of Bangladesh and displace 15 million people. Therefore, it is crucial to determine the effects of different factors on global warming and take possible actions to reduce the damage. Among various factors, natural fires are believed to be responsible for up to 20% of greenhouse gas production in the world. The source of 80% of fresh water in the United States is believed to be forest lands, which means the effect of natural fires can be disastrous not only for drinking water but also for aquatic habitats. In this paper, we present a survey on the impacts of forest fires on global warming.