KERENTANAN SOSIAL DAN EKONOMI PADA BENCANA BANJIR DI KELURAHAN SUTOJAYAN KABUPATEN BLITAR

Yulis Bigandata, Purbudi Wahyuni, Yohana Noradika Maharani
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Abstract

Social and economic vulnerability describes the social and economic fragility of an area due to the influence of hazards, threats and disasters that have the potential to damage, disrupt. This study aims to analyze the social and economic vulnerability of the flood disaster in Sutojayan Village, Blitar Regency. Data on social vulnerability is seen from gender, age, rural/urban, education, disability, transportation, and number of households, and economic vulnerability is seen from unemployment and livelihoods. This study uses a mixture of qualitative and quantitative methods with data obtained through interviews of 5 subjects, a questionnaire of 335 people, and documentation using population data of 7048 people. Data analysis techniques to measure social and economic vulnerability using multiple linear regression and SoVI techniques with the help of CFA. The results showed that: (1) The level of social and economic vulnerability in the post-flood disaster was influenced by indicators: gender, age, education, disability, transportation, and livelihood, and (2) The level of social and economic vulnerability in the post-flood disaster was in the high and medium categories. The Sutojayan environment with a SoVi value of 0.229 has a higher level of vulnerability than the Gondang Legi and Purworejo environments, and (3) The dominant variables that affect the level of social and economic vulnerability in the flood disaster are disability, the number of motorized vehicles, and the number of non-motorized vehicles.
社会和经济脆弱性是指一个地区由于可能造成破坏和破坏的危害、威胁和灾害的影响而具有的社会和经济脆弱性。本研究旨在分析布列塔县苏托加延村洪水灾害的社会和经济脆弱性。关于社会脆弱性的数据从性别、年龄、农村/城市、教育、残疾、交通和家庭数量来看,经济脆弱性从失业和生计来看。本研究采用定性与定量相结合的方法,通过访谈5人,问卷调查335人,文献资料7048人。在CFA的帮助下,使用多元线性回归和SoVI技术来测量社会和经济脆弱性的数据分析技术。结果表明:(1)灾后社会经济脆弱性水平受性别、年龄、受教育程度、残疾程度、交通和生计等指标的影响;(2)灾后社会经济脆弱性水平处于高、中等水平。Sutojayan环境的SoVi值为0.229,其脆弱性水平高于贡当Legi和Purworejo环境。(3)影响洪涝灾害社会经济脆弱性水平的主要变量是残疾、机动车保有量和非机动车保有量。
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