Judul: Pemetaan Sebaran Mangrove Di Pantai Lontar, Provinsi Banten
Abstrak: Terancamnya keberadaan mangrove akibat tingginya tingkat abrasi di Pantai Lontar, Kecamatan Tirtayasa, Serang, Banten memerlukan pemantauan secara berkala agar tidak terjadi degradasi terhadap keberadaan ekosistem mangrove disana. Penelitian ini bertujuan untuk memetakan sebaran kerapatan serta luasan mangrove di Pantai Lontar menggunakan Citra Sentinel-2A. Algoritma indeks kerusakan mangrove (IM) dan mangrove vegetation index (MVI) digunakan untuk membedakan antara vegetasi mangrove dan bukan mangrove, sedangkan algoritma normalized difference vegetation index (NDVI) digunakan untuk memetakan sebaran kerapatan mangrove. Klasifikasi yang dilakukan dengan menggunakan maximum likelihood menghasilkan 3 kelas kerapatan yaitu rapat (13,16 ha), sedang (8,69 ha), dan jarang (7,51 ha), dengan dominansi kelas rapat pada wilayah kajian. Luas total mangrove di Pantai Lontar pada tahun 2022 sebesar 29,41 ha. Uji akurasi menggunakan confusion matrix terhadap kerapatan mangrove menghasilkan akurasi sebesar 93,33% dengan koefisien kappa sebesar 0,900. Uji korelasi persentase tutupan kanopi mangrove antara nilai NDVI dan data lapang menghasilkan koefisien korelasi (r) sebesar 0,90 serta koefisien determinasi (R2) sebesar 0,81., The threat to the existence of mangroves due to the high level of abrasion on Lontar Beach, Tirtayasa District, Serang, Banten requires regular monitoring so that there is no degradation of the existence of the mangrove ecosystem. This study aimed to map the distribution of mangrove density and area on Lontar Beach using Sentinel-2A Imagery. The mangrove damage index (IM) and mangrove vegetation index (MVI) algorithms are used to distinguish between mangrove and non-mangrove vegetation, while the normalized difference vegetation index (NDVI) algorithm is used to map the distribution of mangrove density. Classification carried out using maximum likelihood resulted in 3 density classes, namely dense (13,16 ha), medium (8,69 ha), and rare (7,51 ha), with the dominance of dense classes in the study area. The total area of mangroves in Lontar Beach in 2022 is 29.41 ha. The accuracy test using the confusion matrix on mangrove density resulted in an accuracy of 93.33% with a kappa coefficient of 0.900. A Correlation test of the percentage of mangrove canopy cover between NDVI values and field data resulted in a correlation coefficient (r) of 0.90 and a coefficient of determination (R2) of 0.81.
Keyword: Kerapatan Mangrove, NDVI, Pantai Lontar, Penginderaan Jauh, Sentinel-2A, Lontar Beach, Remote Sensing, Mangrove Density

Judul: Mapping the Area and Density of Mangroves in Pantai Bahagia Village, Muara Gembong District, Bekasi Regency
Abstrak: Penurunan luasan mangrove menyebabkan perlunya pemantauan hutan mangrove untuk mencegah terjadinya dampak keberlanjutan dari degradasi lahan mangrove di pesisir Desa Pantai Bahagia, Kecamatan Muara Gembong, Kabupaten Bekasi. Penelitian ini bertujuan mengidentifikasi dan memetakan luas sebaran dan kerapatan mangrove di Desa Pantai Bahagia. Analisis Normalized Difference Vegetation Index (NDVI) digunakan untuk mengetahui kerapatan mangrove di suatu area. Kerapatan mangrove yang dihasilkan terklasifikasi menjadi 3 kelas kerapatan, yaitu mangrove jarang (0,693 km2), mangrove sedang (0,562 km2), dan mangrove rapat (1,865 km2) dengan total luasan mangrove sebesar 3,12 km2. Hasil uji akurasi confusion matrix pada klasifikasi citra memperoleh nilai akurasi sebesar 86,58% dan kappa coefficient sebesar 0,697. Pengujian korelasi persentase tutupan kanopi mangrove yang diperoleh dari data lapang dengan nilai NDVI dilakukan menggunakan metode regresi linier sederhana dan menghasilkan koefisien korelasi (r) dengan nilai 0,834 dan koefisien determinasi (R2) dengan nilai 0,696., Mangrove areas decreasing lead to the need for monitoring of mangrove forests to prevent the impacts of mangrove area degredation that occured in the coast of Pantai Bahagia Village, Muara Gembong District, Bekasi Regency. This research aimed to compute and make distribution area and density map of mangrove in Pantai Bahagia Village. Normalized Difference Vegetation Index (NDVI) analysis is used to determine the density of mangroves in certain area. The results were classified into 3 classes, sparse (0,693 km2), moderate (0,562 km2), and dense (1,865 km2) with a total mangrove area of 3,12 km2. The confusion matrix accuracy test results were consisted with an accuracy value of 86.58% and kappa coefficient of 0.697. The correlation test of mangrove canopy cover percentage obtained from field data with NDVI value was conducted using a simple linear regression method. The results were 0.834 for coefficient of correlation (r) and 0.696 for coefficient of determination (R2).
Keyword: Pantai Bahagia Village, Density, Mangrove, NDVI, Remote sensing

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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