Judul: Estimation of Mangrove Canopy Cover using Unmanned Aerial Vehicle (UAV) in Indramayu Regency, West Java
Abstrak: Mangrove memiliki peranan penting dalam menjaga ekosistem pesisir. Peranan penting ini mencakup fungsi fisik, fungsi biologi, dan ekonomi. Kabupaten Indramayu merupakan salah satu daerah di pantai utara jawa dengan panjang garis pantai 147 km. Menurunnya tutupan mangrove di Kabupaten Indramayu tidak lepas dari pembukaan lahan untuk tambak sehingga kegiatan monitoring penting untuk melihat kondisi mangrove secara berkelanjutan. Salah satu upaya pemantauan kondisi mangrove dilakukan dengan menggunakan pesawat tanpa awak untuk mengatasi kendala dana dan kesulitan survei lapang. Penelitian ini bertujuan menduga tutupan tajuk mangrove berdasarkan nilai NDVI citra berbasis pesawat tanpa awak (UAV). Penelitian ini dilakukan di Indramayu pada bulan Maret 2021. Pengumpulan data dilakukan menggunakan pesawat tanpa awak (Unmanned Aerial Vehicle / UAV) dengan sensor multispektral (Red, Green, Red Edge dan NIR). Hasil penelitian ini menunjukkan bahwa model regresi terbaik untuk menduga tutupan tajuk mangrove adalah regresi eksponensial dengan dengan persamaan LAI = 0,1535e1,9458NDVI dengan R2 = 0,636 Model penduga ini dapat digunakan untuk monitoring mangrove secara berkala. Data monitoring yang akurat sangat berguna dalam penyusunan kebijakan dan strategi pengelolaan sebagai upaya mempertahankan juga meningkatkan fungsi dan jasa ekosistem mangrove., Mangroves have an important role in maintaining coastal ecosystems. These important roles include physical, biological, and economic functions. Indramayu regency is one of the areas on the north coast of Java with a coastline length of 147 km. The decrease of mangrove cover in Indramayu Regency cannot be separated from the land clearing for fish pond, therefore monitoring activity is important to see the suitainability management mangroves. Alternative ways to monitor mangrove condition is using an unmanned aerial vehicle (UAV) to overcome the budget constraint and difficulties of doing field surveys. The study aims to estimate the mangrove canopy cover based on the NDVI derive from multispectral drone-based imagery (UAV). The research was conducted in Indramayu in March 2021. Data collection is done using unmanned aerial vehicles (UAV) with multispectral sensors (Red, Green, Red Edge, and NIR). The study shows that the best canopy cover estimator model is exponential regression with the equation of CC = 0.1535e1.9458NDVI with R2 = 0.636. The model can be used for monitoring mangroves periodically. Accurate monitoring data will be very useful in the preparation of policies and management strategies to maintain and improve the functions and services of mangrove ecosystem.
Keyword: mangrove, monitoring, pendugaan, tutupan tajuk

Judul: Mangrove Canopy Cover Analysis using High Resolution Multispectral Image
Abstrak: Penginderaan jauh merupakan sumber data penting untuk memperkirakan tutupan vegetasi pada wilayah yang luas dan dapat dimafaatkan dalam menentukan tutupan kanopi mangrove. Tujuan dari penelitian ini adalah menganalisis klasifikasi tutupan lahan menggunakan citra foto udara, menganalisis tutupan kanopi vegetasi mangrove dari sensor satelit SPOT6, dan mengevaluasi perbandingan tutupan kanopi dari SPOT 6 dan tutupan lahan dari citra foto udara. Software yang digunakan dalam penelitian ini adalah Software Agisoft Metashape Professional, eCognition Developer, dan ArcMap 10.4. Analisis yang digunakan yaitu analisis vegetasi NDVI yang dikorelasikan dengan persentase tutupan kanopi mangrove. Hasil analisis didapatkan R2 dari ketiga lokasi yaitu Pabeanudik sebesar 0,9334 (93%), Karangsong sebesar 0,8855 (88%), dan Loasarang sebesar 0,8718 (87%). Hasil tersebut menandakan bahwa korelasi antara analisis vegetasi (NDVI) dengan persentase tutupan mangrove sangat baik., Remote sensing is an important data source for estimating vegetation cover over a large area and can be used to determine mangrove canopy cover. The purpose of this study was to analyze land cover classification using drone imagery, analyze mangrove vegetation canopy cover from SPOT6 satellite sensors, and evaluate the comparison of canopy cover from SPOT 6 and land cover from drone images. The software used in this research is Agisoft Metashape Professional Software, eCognition Developer, and ArcMap 10.4. The analysis used is NDVI vegetation analysis which is correlated with the percentage of mangrove canopy cover. The results of the analysis obtained R2 from the three locations, namely Pabeanudik of 0.9334 (93%), Karangsong of 0.8855 (88%), and Loasarang of 0.8718 (87%). These results indicate that the correlation between vegetation analysis (NDVI) and the percentage of mangrove cover is very good.
Keyword: Mangrove canopy, Remote sensing, Segmentation

Judul: Synthesis of Apatite - Chitosan Composite Using Duck Eggshell and Chitosan with Temperature and pH Control
Abstrak: Composite of apatite-chitosan was prepared by using chitosan as polymer matrix. Calcium phosphate was prepared from CaO and (NH4)2HPO4, which the ratio Ca : P had to be 1.67. Chitosan is produced by deacetilase from biopolymer chitin. Duck eggshell (95% CaCO3) as starting material was converted to be calcium oxide (CaO) through calcinations with temperature 1000oC for 5 hours. In-situ and ex-situ methods were prepared from apatite and chitosan (dissolved with acetate acid 2%). Calcium phosphate prepared for bone implantation, but it is too fragile and brittle to be implant into the body. So addition of chitosan can decrease crystalinity and increase mechanic characteristic (tougher). Composite apatite-chitosan was resulted by fast precipitation. Fast precipitation was held in a breaker glass with nitrogen atmosphere, under controlled temperature at 37oC and pH 7, in order to increase amount of hydroxyapatite. Precipitation with CaO which was dropped by (NH4)2HPO4. Hydroxyapatite and chitosan were appearing at samples with in-situ and ex-situ methods which indicating by peak matching of XRD (closed lattice parameter, crystal size), overlapping at FTIR spectra and supporting by SEM picture (homogenous and agglomerated particle). However, it still needs further research to examine biocompatibility osteoconductive degree of sample by in-vivo and in-vitro test.
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