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首页> 外文会议>2017 15th International Conference on Quality in Research : International Symposium on Electrical and Computer Engineering >An analysis of natural disaster data by using K-means and K-medoids algorithm of data mining techniques
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An analysis of natural disaster data by using K-means and K-medoids algorithm of data mining techniques

机译：利用数据挖掘技术的K-means和K-medoids算法分析自然灾害数据

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Indonesia is one of the countries with diverse morphology of the lands, high mountains, and the tropical climates of frequent high rainfall. This condition often causes natural disasters in some areas of the country, which sometimes are so terrible that make a lot of people are missing and suffering. In order to reduce the impact of natural disasters to the people and environment, a research was conducted by capturing data showing the occurrence of the disasters and data about the weather conditions for the last five years. Data is obtained from the official sites of Indonesian National Board for Disaster Management (BNPB) and Indonesian Agency for Meteorological, Climatological, and Geophysics (BMKG). This data is then analyzed by using clustering data mining techniques i.e. k-means algorithm and k-medoids algorithm. The two methods are frequently used to make some analysis of data to find some hidden information. The result shows that weather is not the only factor causing natural disaster. By using the result, the government can make some plans for natural disaster mitigations.
机译：印度尼西亚是土地形态，高山和频繁降雨的热带气候的国家之一。这种情况通常会在该国某些地区造成自然灾害，有时如此可怕，以致许多人失踪和遭受痛苦。为了减少自然灾害对人类和环境的影响，通过捕获显示灾难发生的数据和有关过去五年的天气状况的数据进行了研究。数据来自印度尼西亚国家灾难管理委员会（BNPB）和印度尼西亚气象，气候与地球物理机构（BMKG）的官方站点。然后，通过使用聚类数据挖掘技术（即k-means算法和k-medoids算法）来分析此数据。经常使用这两种方法对数据进行一些分析，以找到一些隐藏的信息。结果表明，天气不是造成自然灾害的唯一因素。通过使用结果，政府可以制定一些减轻自然灾害的计划。

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