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The impact of disasters can disrupt people’s lives, both natural and non-natural, resulting in human casualties, environmental damage, property loss, and psychological impact. Besides that, disasters that occur can also cause damage to health facilities, worship, education, and damage to homes, both severely, moderately, and lightly. The impact of disasters is so large, so a logistics warehouse is needed to handle the disaster. One of the countries prone to disasters, Indonesia which has the fourth largest population in the world with 34 provinces and 502 regions or cities. The purpose of this research is to determine the clustering of areas in Indonesia with a very high-risk, high-risk, moderate risk, low risk, and very low risk of disaster based on disaster data in Indonesian National Agency for Disaster Managementin 2010-2019 using K-Means calculations by Excel and the RapidMiner application. The results of both clustering methods are 6 cities that have a very high-risk index, 79 cities that have a high-risk index, 29 cities that have a medium risk index, 19 cities that have a low-risk index, and 369 cities have a very low-risk index. Thisresult can be considered for the construction of logistics warehouses for disaster management and K-Means method also can be used to know the clustering risk.

The Micro, Small and Medium Enterprises (MSMEs) still have low involvement in being environmentally friendly. Production processes that are associated with environmental pollution, such as the use of hazardous materials, and produce waste that are not properly managed, threaten sustainability. This study aims to determine the driving and inhibiting factors of the green management implementation in the micro, small and medium industries in the city of Banda Aceh. The data used in this study were obtained from perception of 60 MSME doer which randomly selected from 208 MSMEs, according to Office of Cooperative, MSME and Trade of Banda Aceh, in 9 sub districts of Banda Aceh represent the perception of entrepreneurs. Perception of 10 employees of Office Environmental Service, Cleanliness and Beauty of Banda Aceh and also perception of 10 academics or environmental activist representing perception of government and experts. Fuzzy TOPSIS method is used to rank the driver and inhibitor factors. The study found that the five highest driver factors for green management application which are: regulation and law enforcement, employees' awareness and motivation, ability to increase competitiveness, customer demand for environmentally friendly products, knowledge about technology and environment-friendly innovations that can be adopted. Meanwhile, the inhibiting factors are in the aspect of human resources such as low environmental knowledge of employees, lack of training for empowerment, and low ability to adopt technology. Inhibitors from the economic and organizational side are limited financial capacity and the absence of green planning.