Coastal zones are areas that are vulnerable to ecological damage. One type of ecosystem that is vulnerable to damage in coastal zones is mangroves. The coastal area of East Aceh is one of the areas where the existence of mangrove ecosystems has a high level of criticality. The level of criticality of mangroves in the area is caused by various factors such as exploitation of natural resources, physical development such as residential areas, and conversion of land to other designation areas without considering to the sustainability of mangrove ecosystems. By utilization of Landsat 8 and Bing Map Imagery satellite image data using the concept of geographic information systems, the extent of mangrove forest and its critical level can be inventoried. Determination of the critical level of mangrove forests was carried out by referring to the mangrove inventory guidelines issued by the Indonesian Ministry of Forestry in 2005. The results of data processing showed that the critical level of mangrove forests reached 4,200.02 hectares in severely damaged conditions, 7,286.93 hectares in damaged condition, and 9.704, 01 hectares are not damaged. Based on these results, forest management efforts are needed through the method of rehabilitating mangrove forests toimprove the condition of heavily damaged mangrove forests.

Abstrak. Hutan mangrove di pesisir Kota Langsa semakin lama semakin terancam keberadaannya. Penyalahgunaan hutan mangrove yang dilakukan dalam kurun waktu akhir-akir ini telah menimbulkan berbagai kerusakan sehingga menyebabkan tingkat kekritisannya semakin tinggi. Salah satu upaya yang dapat dilakukan untuk mengatasi hal tersebut adalah dengan memanfaatkan teknologi spasial. Teknologi spasial merupakan salah satu media yang penting untuk melakukan perencanaan pembangunan dan pengelolaan sumber daya alam dengan cakupan yang luas. Penelitian ini bertujuan untuk mengetauhi seberapa besar tingkat kekrtitisan hutan mangrove sehingga dapat dilakukan upaya pemulihan bagi hutan mangrove dengan tingkat kekritisan yang tinggi. Kriteria yang digunakan untuk mengetahui tigkat kekrtitisan hutan mangrove yaitu jenis penggunaan lahan, kerapatan tajuk tanaman, dan ketahanan tanah terhadap abrasi. Hasil penelitian menunjukkan hutan mangrove dengan tingkat kekritisan tertinggi terjadi di kawasan pesisir Langsa bagian timur dengan kategori sangat kritis seluas 453,25 Ha atau 42,16 %, sedangkan hutan mangrove yang termasuk kategori kritis seluas 1.108,99 Ha atau 44%, serta yang tegolong ke dalam kategori tidak kritis seluas 2.337,78 Ha atau 56.70%.Critical Level of Mangrove Forest Using Spatial Technology Case Study in Coastal Areas of LangsaAbstract. Mangrove forests in coastal areas of Langsa are increasingly threatened. The misuse of mangrove forests that have been carried out at the end-time period has caused various damage, causing the critical level to be higher. One effort that can be done to overcome this problem is to utilize spatial technology. Spatial technology is one of the important media for carrying out extensive development planning and natural resource management The purpose of this study is to determine the critical level of mangrove forests so that recovery efforts can be done for mangrove forests with highest criticality level. The criteria used to determine the critical level of mangrove forests are the type of land use, forest canopy density, and soil resistance to abrasion. The results showed that the highest critical level of mangrove forest occurred in the eastern coastal areas of Langsa with very critical category is 453.25 ha or 42.16%, mangrove forests included in the critical category is 1,108.99 ha or 44%, and those classified to the non-critical category is 2,337.78 ha or 56.70%.

Regresi logistik multinomial merupakan perluasan dari regresi logistik biner yang memungkinkan lebih dari dua kategori variabel dependen. Pada paper ini akan membahas penaksiran parameter regresi logistik multinomial melalui Generalized Method of Moment  (GMM). Generalized Method of Moment (GMM) merupakan salah satu metode yang dapat mengatasi pelanggaran asumsi pada data seperti autokorelasi dan heteroskedastisitas