TEACHER PERSPECTIVES ON HIGH SCHOOL IN ACEH PROVINCE ABOUT NATURAL DISASTERS
Abstract
The Indonesian government has made efforts to restore the structure and development of school responses, including increasing knowledge, skills, and disaster management operating systems in schools. School leaders and teachers are expected to balance the need for standard operating procedures with the ability of organizational structures to respond to specific problems caused by disasters. Teacher enhancement is expected to provide a more active role for students and overcome their stress in post-disaster situations. This study aimed to examine the perspective of high school teachers on knowledge of natural disasters and natural disaster mitigation. A descriptive statistical approach is used to describe and explain teacher knowledge and mitigate natural disasters. Explaining how much influence or relationship between teachers' knowledge on disaster mitigation is done. The sample in this study was high school teachers in Aceh province, with 389 teachers. The research data collection used an instrument in the form of a questionnaire. The results showed that the perspective of high school teachers regarding knowledge of natural disasters was in the high category on average; the average teacher knew general knowledge of natural disasters, signs of catastrophe, classification of natural disasters, and causes of natural disasters. Not much different from the results of the teacher's perspective regarding natural disaster mitigation in the very high category, planning in the mitigation process, policies, operational disaster procedures, signs of disaster evacuation have been recognized by SMA teachers in Aceh province. The level of knowledge of high school teachers with mitigation has a significant relationship, so the higher the knowledge of high school teachers about natural disasters, the more high-school teachers can mitigate against natural disasters.
Keywords: Teacher's Perspective, Natural Disaster Knowledge, Natural Disaster Mitigation, Regression Analysis
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DOI: https://doi.org/10.24114/jg.v13i2.23863
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