利用K-Means对印度尼西亚自然灾害易发地区进行分类

International Journal of Grid and Distributed Computing Pub Date : 2018-08-31 DOI:10.14257/ijgdc.2018.11.8.08

B. Supriyadi, A. Windarto, Triyuni Soemartono, Mungad

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引用次数: 73

摘要

自然和人为因素共同造成的灾害，造成了人员伤亡、环境破坏、财产损失和心理影响。该研究的目的是对印度尼西亚的灾害易发地区进行分类，使用快速采矿工具中实施的K-means聚类方法。这些数据是从中央统计局收集的，关于2008-2014年印度尼西亚各省被认为容易发生自然灾害的村庄数量。样本数据为印度尼西亚34个省，通常发生3种自然灾害，即洪水、地震和滑坡。研究的最终结果为:(1)4个省被划分为高等级，集群中心为1363.333(洪水)、528.25(地震)和949.583(滑坡);14个省被划分为中等，集群中心为142.619(洪水)、96.071(地震)和72.048(滑坡);16个省为低等级，集群中心分别为507.396(洪水)、57.604(地震)和177.479(滑坡)。这项工作可以通过绘制易发灾害地区的地图，特别是亚齐、西爪哇、中爪哇和东爪哇等4个自然灾害非常严重的省份，进一步为印度尼西亚政府提供投入。

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Classification of Natural Disaster Prone Areas in Indonesia using K-Means

Disaster caused by both nature and human factors has resulted in the occurrence of human casualties, environmental damage, property loss, and psychological impact. The study aims to classify disaster prone areas in Indonesia using K-means clustering method implemented in rapid miner tools. The data are collected from the Central Bureau of Statistics about the number of villages that considered as natural disaster-prone by province in Indonesia in years 2008-2014. The sample data are 34 provinces in Indonesia with 3 natural disasters commonly happen i.e. namely: Flood, Earthquake and Landslide. The final outcomes of the study were: (1) 4 provinces classified as High with cluster center 1363.333 (flood), 528.25 (earthquake) and 949.583 (landslide); 14 provinces classified as Medium with cluster center 142.619 (flood), 96.071 (earthquake) and 72.048 (landslide); and 16 provinces classified as Low with cluster center 507.396 (flood), 57.604 (earthquake) and 177.479 (landslide). This work can further provide input to the Indonesia government through mapping of disaster prone areas especially 4 provinces with very high natural disasters such as Aceh, West Java, Central Java and East Java.

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来源期刊

International Journal of Grid and Distributed Computing COMPUTER SCIENCE, SOFTWARE ENGINEERING-

自引率

0.00%

发文量

期刊介绍： IJGDC aims to facilitate and support research related to control and automation technology and its applications. Our Journal provides a chance for academic and industry professionals to discuss recent progress in the area of control and automation. To bridge the gap of users who do not have access to major databases where one should pay for every downloaded article; this online publication platform is open to all readers as part of our commitment to global scientific society. Journal Topics: -Architectures and Fabrics -Autonomic and Adaptive Systems -Cluster and Grid Integration -Creation and Management of Virtual Enterprises and Organizations -Dependable and Survivable Distributed Systems -Distributed and Large-Scale Data Access and Management -Distributed Multimedia Systems -Distributed Trust Management -eScience and eBusiness Applications -Fuzzy Algorithm -Grid Economy and Business Models -Histogram Methodology -Image or Speech Filtering -Image or Speech Recognition -Information Services -Large-Scale Group Communication -Metadata, Ontologies, and Provenance -Middleware and Toolkits -Monitoring, Management and Organization Tools -Networking and Security -Novel Distributed Applications -Performance Measurement and Modeling -Pervasive Computing -Problem Solving Environments -Programming Models, Tools and Environments -QoS and resource management -Real-time and Embedded Systems -Security and Trust in Grid and Distributed Systems -Sensor Networks -Utility Computing on Global Grids -Web Services and Service-Oriented Architecture -Wireless and Mobile Ad Hoc Networks -Workflow and Multi-agent Systems