Kesesuaian budidaya keramba jaring apung (KJA) ikan kerapu di perairan Teluk Sabang Pulau Weh, Aceh

Weh Island is one of the coastal region that has high prospect in fisheries, one of it is floating net cage. Unfortunately, the unavailability of the classification zone for fish net culture and the oceanographic conditions of the coastal water become the main issues of the success of the fish net cage (KJA) culture activities.  The aim of this study is analyze suitability of floating net cage culture for grouper in Sabang Bay. The method use in this research is Inverse Distance Weighted (IDW) method. There were 10 water quality variabels measured, such as protection, bathimetry, water transparency, current velocity, temperature, salinity, pH, dissolved oxygen, nitrate and phosphate. Area suitability divided into three suitability criteria, i.e very suitable, suitable and not suitable were used to determine the suitability of floating net cage. The result of the analysis are obtained show that the area for grouper culture Sabang Bay covering 11.3 % or 9.08 Ha of Sabang Bay were classified as very suitable (S1), suitable class (S2) covering an area of 39.8 % or 32.08 Ha of Sabang Bay, and not suitable class (N) covering 49 % or 39.54 Ha of Sabang Bay. Based on this percentage can be concluded that some of the coastal of the Sabang Bay can be utilized as a floating net cage culture of grouper fish activities.Keywords: Grouper culture, GIS, Suitability, Sabang Bay, Aceh Province ABSTRAKPulau Weh merupakan salah satu wilayah yang memiliki potensi perikanan yang cukup besar. Akan tetapi dengan belum tersedianya penentuan lokasi budidaya keramba jaring apung serta data kondisi perairan yang tersedia menjadi kendala utama dalam peningkatan keberhasilan dan pengembangan budidaya keramba jaring apung (KJA). Penelitian ini bertujuan untuk menganalisis luasan kesesuaian perairan budidaya keramba jaring apung ikan kerapu di perairan Teluk Sabang. Metode yang digunakan pada penelitian ini adalah metode Inverse Distance Weighted (IDW). Terdapat sepuluh parameter yang diukur, yaitu keterlindungan, kedalaman, kecerahan, kecepatan arus, suhu, salinitas, pH, oksigen terlarut, nitrat dan fosfat. Tingkat kesesuaian perairan dibagi menjadi 3 (tiga) kelas kesesuaian, yaitu sangat sesuai, sesuai dan tidak sesuai. Hasil analisis yang didapat menunjukkan bahwa luasan untuk budidaya ikan kerapu Teluk Sabang sangat sesuai (S1) seluas 9,08 % atau 11,3 Ha dari Teluk Sabang, kelas sesuai (S2) seluas 39,8 % atau 32,08 Ha dari Teluk Sabang, dan kelas tidak sesuai (N) seluas 49 % atau 39,54 Ha dari Teluk Sabang. Berdasarkan persentase tersebut dapat diambil kesimpulan bahwa sebagian perairan Teluk Sabang dapat dimanfaatkan sebagai usaha budidaya keramba jaring apung ikan kerapu.Kata kunci: Budidaya ikan kerapu, SIG, Kesesuaian perairan, Teluk Sabang, Provinsi Ace

Improving Community Capacity in Rapid Disaster Mapping: An Evaluation of Summer School

Experiences with natural disasters have intensified recent efforts to enhance cooperation mechanisms among official disaster management institutions to community participation. These experiences reveal a need to enhance rapid mapping technical assistance to be developed and shared among young scientists through a summer school. However, the question arose of how effective this summer school to be used as a tool to increase scientists’ understanding and capacity. This study sought to evaluate the extent to which human resource capacity building can be effectively implemented. The methods used for this evaluation is through observations, questionnaires and a weighted scoring based on knowledge, skills and attitudes’ criteria. The results indicate a significant improvement in knowledge (94.56%), skills (82%) and attitudes (85.20%) among the participants. Even though there are still gaps in participants’ skills, the summer school was found to be an effective way to train the young scientists for rapid mapping

DIVERSITY AND SIMILARITY OF REEF PROFILE FORM BASED ON REEF FISHES AND REEF LIFEFORM IN DEPAPRE BAY JAYAPURA, PAPUA PROVINCE, INDONESIA

Pemahaman tentang keanekaragaman, dan asosiasi di dalamnya khususnya ikan karang sangat penting dalam rangka pengelolaannya secara berkelanjutan. Tujuan penelitian ini adalah mengkaji struktur komunitas dan kemiripan berdasarkan kelimpahan famili ikan karang dengan bentuk lifeform. Pengambilan data lifeform menggunakan metode Point Intercept Transect, dan pengambilan data ikan karang menggunakan metode Underwater Visual Census. Analisis Korespondensi digunakan untuk menggambarkan kemiripan kelimpahan famili ikan karang dan lifeform karang dengan bentuk profil terumbu. Hasil penelitian menunjukan bahwa total ikan karang yang dijumpai untuk ikan indikator dan ikan target sejumlah 3.666 ekor yang terdiri dari 130 spesies dari 26 famili, kelimpahan individu ikan target tertinggi secara berturut-turut Tanjung Tanah Merah, Tanjung Harlem, Pulau Kwahkeboh, Tanjung Sarebo, Amayepa, Tanjung Amay dan Tanjung Kuburan Tablasufa. Keanekaragaman (H’) relatif tinggi, yakni berkisar 2,66-3,63, Indeks Keseragaman (E)  cukup tinggi yakni berkisar 0,55-0,76 (→1), dan Indeks Dominansi (D) rendah yakni berkisar 0,03-0,08 (→0). Kelimpahan famili ikan  karang dan lifeform memiliki kemiripan pada bentuk profil terumbu.Understanding of diversity, and associations in it, especially reef fish, is very important in the framework of sustainable management. The purpose of this study is to examine the community structure and its similarity based on family abundance of reef fishes and the lifeform. Retrieval of lifeform data using the Point Intercept Transect method, and collection of  reef fishes data using the Underwater Visual Census method. Correspondence Analysis is used to describe the similarity of the abundance of reef fishes families and lifeforms to reef profile. The results showed that the total number of reef fish found for indicator fish and targeted fish at 3,666 individuals consisting of 130 species from 26 families, abundance of individuals of the highest target fishes at Tanah Merah Cape, Harlem Cape, Kwahkeboh Island, Sarebo Cape, Amayepa, Amay Cape and Kuburan Tablasufa Cape. Diversity (H') is relatively high, which is around 2.66-3.63, the Similarity Index (E) is quite high, which ranges from 0.55 to 0.76 (→1), and the Dominance Index (D) is low which ranges 0.03-0.08 (→0). The abundance of reef fishes families and lifeform has similarity to reef profiles

Resiliensi nelayan terhadap ketersediaan sumberdaya perikanan di Kepulauan Karimunjawa

Resilience is a concept that cannot be generalized. This is because in analyzing resilience, the parameters that have been used for the resilience analysis is depend on the resilience context itself. It is important to establish which parameters are most important to be used for analyzing resilience of fishermen related to fisheries resources. Fishers' are the most vulnerable community and have a high depencency on natural resources. It is necessary to analyze of fishers' resiliences.  The resilient fishing communities can increase their capacity to cope on socio-economic change. The purpose of this study is to determine the parameters that can be used to analyze resilience of the fishermen in small islands. The study was conducted from February to April 2018. The method used in this studyis expert judgment. Based on previous studies to analyze resilience used 6 dimensions, namely: social (21 parameters), economic (26 parameters), institutional (13 parameters), infrastructure (12 parameters), resources (9 parameters), and potential disaster (2 parameters), the total parameters are 83 parameters. Based on the result, 83 parameters were being indexing and only 53 parameters having values above 3,50 are used to analyze resilience assessment. The parameters that have the highest index in each dimension are the level of poverty (social dimension), number of livelihood (economic dimension), government role (institutional dimension), and fish catch (resource dimension).The selected parameters are used to analyze the fisher’s resilience in Karimunjawa islands

Algorithm for detecting deforestation and forest degradation using vegetation indices

In forestry sector, the remote sensing technology hold a key role on forest inventory and monitoring their changes. This paper describes the algorithm for detecting deforestation and forest degradation using high resolution satellite imageries with knowledge-based approach. The main objective of the study is to develop a practical technique for monitoring deforestation and forest degradation occurred within the mangrove and swamp forest ecosystem.  The SPOT 4, 5, and 6 images acquired in 2007, 2012 and 2014 were transformed into three vegetation indices, i.e., Normalized Difference Vegetation Index (NDVI), Green-Normalized Difference Vegetation index (GNDVI) and Normalized Green-Red Vegetation index (NRGI).  The study found that deforestation was well detected and identified using the NDVI and GNDVI, however the forest degradation could be well detected using NRGI, better than NDVI and GNDVI.  The study concludes that the strategy for monitoring deforestation, biomass-based forest degradation as well as forest growth could be done by combining the use of NDVI, GNDVI and NRGI respectively

The Examination of The Satellite Image-Based Growth Curve Model Within Mangrove Forest

Developing growth curve for forest and environmental management is a crucial activity in forestry planning. This paper describes a proposed technique for developing a growth curve based on the SPOT 6 satellite imageries. The most critical step in developing a model is on pre-processing the images, particularly during performing the radiometric correction such as reducing the thin cloud. The pre-processing includes geometric correction, radiometric correction with image regression, and index calculation, while the processing technique include training area selection, growth curve development, and selection. The study found that the image regression offered good correction to the haze-distorted digital number.  The corrected digital number was successfully implemented to evaluate the most accurate growth-curve for predicting mangrove.  Of the four growth curve models, i.e., Standard classical, Richards, Gompertz, and Weibull models, it was found that the Richards is the most accurate model in predicting the mean annual increment and current annual increment.  The study concluded that the growth curve model developed using high-resolution satellite image provides comparable accuracy compared to the terrestrial method.  The model derived using remote sensing has about 9.16% standard of error, better than those from terrestrial data with 15.45% standard of error