<![CDATA[Most part of Indonesian coastal areas are vulnerable to inundation potential due to global sea level rise. This inundation is predicted to cause permanent flood and worsen abrasion along coastal zone where many populations live, also will threaten impor-tant infrastructures and economic assets, as well as well known tourism areas. To anticipate these various harming potential impacts, planning of adaptation to climate change is needed. In order to achieve the appropriate and effective adaptation planning, coastalvulnerability pattern needs to be recognized first, so that to suit the region’s characteristics. To recognize this coastal vulnerability pattern, certain similar characteristics need to be found represented by a group of indicators. Therefore, a method of analysis which is able to classify information into a certain group based on several similar characteristics is needed, that is so called as cluster method. By using cluster method and through iterative experiments, this study has succeeded in identifying coastal vulnerability patterns to inundation caused by global sea level rise. The experiments concluded that there are five indicators which clearly control the coastal vulnerability pattern; they are inundation area, infrastructures, population density, built area, and non-settlement area. This study also concludes that of the 325 districts/cities on Indonesian coastal, they can be classified into six patterns of vulnerability. Twenty three districts/cities among them (7.07%) are classified as highly vulnerable cluster, which generally characterized as high inunda-tion ratio value, high infrastructures value, high population density value, high settlement areas value, and low non-settlement areas value. Thus, several adaptation options consist of population control, revision of coastal spatial plans, and adjustment of infra-structures.]]>
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