Judul: Analysis of Mangroves Density and Health in Mundupesisir, Mundu District, Cirebon Regency
Abstrak: Mangrove merupakan jenis tumbuhan yang memiliki fungsi penting terhadap ekosistem khususnya di daerah pesisir yang menjadi area pasang surut. Pada tahun 2022, 90% mangrove di Pantai Utara Jawa Barat mengalami kerusakan, salah satunya di Kabupaten Cirebon. Kerusakan mangrove menyebabkan perlunya pemantauan kondisi hutan mangrove untuk mencegah dampak berkelanjutan di Mundupesisir, Kecamatan Mundu, Kabupaten Cirebon. Penelitian ini bertujuan untuk memetakan serta menganalisis kerapatan dan kesehatan mangrove di Mundupesisir. Analisis kerapatan mangrove dilakukan dengan membandingkan uji regresi linear terhadap 5 indeks vegetasi berbeda, dan kesehatan mangrove dianalisis dengan menggunakan algoritma Mangrove Health Index (MHI). Normalized Difference Vegetation Index (NDVI) dipilih menjadi indeks vegetasi kerapatan mangrove dengan nilai koefisien determinasi tertinggi. Nilai koefisien korelasi (r) tutupan kanopi mangrove berdasarkan data survei lapang dengan NDVI sebesar 0,7992 dan koefisien determinasi (R2) sebesar 0,6388, Kerapatan mangrove yang dihasilkan terklasifikasi menjadi 3 kelas kerapatan, yaitu mangrove jarang (1,05 ha), mangrove sedang (0,76 ha) dan mangrove rapat (29,33 ha), serta kesehatan mangrove yang dihasilkan terklasifikasi menjadi 3 kelas kesehatan, yaitu mangrove buruk (2,44 ha), mangrove sedang (22,5 ha), dan mangrove sehat (6,2 ha) dengan total luasan mangrove sebesar 31,14 ha. Hasil uji akurasi confusion matrix pada klasifikasi sebaran kerapatan mangrove memperoleh nilai sebesar 92,86% dan kappa coefficient sebesar 0,74, serta pada klasifikasi sebaran kesehatan mangrove memperoleh nilai 82,14% dan kappa coefficient sebesar 0,49. Metode regresi linear sederhana kembali digunakan untuk melakukan uji korelasi antara persentase tutupan kanopi mangrove dengan menggunakan NDVI, dan kesehatan mangrove. Nilai koefisien korelasi (r) kerapatan mangrove berdasarkan NDVI dengan kesehartan mangrove berdasarkan MHI sebesar 0,7009 dan koefisien determinasi (R2) sebesar 0,4912, Mangrove is a type of plant that has important functions to the ecosystem especially in the coastal areas that are receding areas. By 2022, 90% of the mangroves on the North West Java Coast were damaged, one of them in the district of Cirebon. Mangrove damage has led to the need to monitor the conditions of mangrove forests to prevent sustainable impact in Mundupesisir, Mundu district, Cirebon district. The research aim at mapping and analyzing the density and health of mangroves in the Mundupesisir. The mangrove density analysis was done by comparing the linear regression test to 5 different vegetation index, and the mangrove health was analyzed using the Mangrove Health Index (MHI) algorithm. Normalized Difference Vegetation Index (NDVI) was selected as the vegetation density index of mangrove with the highest determination coefficient value. The value of the correlation coefficient (r) of the coverage of mangrove canopy is based on field survey data with NDVI of 0.7992 and the determination factor (R2) of 0.6388, The mangrove density is classified into 3 density classes, namely rare mangrove (1,05 ha), moderate mangrove (0,76 ha) and dense mangrove (29,33 ha), as well as the mangrove health are classified in 3 health classes, that is unhealthy mangrove (2.44 ha), moderate mangrove (22,5 ha), and healthy mangrove (6.2 ha) with a total mangrove area of 31.14 ha. The confusion matrix accuracy test results on the distribution distribution of mangroves obtained a score of 92.86% and the kappa coefficent of 0.74, and on the classification of health distribution mangrove received
Keyword: Health, Mangrove, MHI, Mundupesisir, NDVI

Judul: Mangrove Vegetation Mapping Using Sentinel-2A Satellite Data Utilizing MVI and NDVI Algorithms on Cirebon Coast
Abstrak: Kondisi ekosistem mangrove yang telah menurun di Desa Mundupesisir, Kecamatan Mundu, Kabupaten Cirebon, Jawa Barat akibat dari kegiatan antropologis. Hal tersebut memunculkan urgensi pemantauan ekosistem mangrove agar kerusakan tidak memburuk. Penelitian ini bertujuan untuk memetakan sebaran, kerapatan, dan luasan mangrove di Desa Mundupesisir menggunakan citra Sentinel-2A. Terdapat 2 algoritma yang digunakan, yaitu algoritma Mangrove Vegetation Index (MVI) dan Normalized Difference Vegetation Index (NDVI). Algoritma MVI digunakan untuk membedakan vegetasi mangrove dan bukan mangrove dengan nilai ambang batas 2.374–19.409. Algoritma NDVI digunakan untuk memetakan sebaran kerapatan mangrove. Klasifikasi menggunakan metode maximum likelihood menghasilkan 3 kelas kerapatan mangrove dengan total luas 23.07 hektar. Kelas kerapatan tersebut terdiri dari kelas rapat (21.31 ha), sedang (0.67 ha), dan jarang (1.07 ha). Uji akurasi menggunakan metode confusion matrix terhadap kerapatan mangrove yang menghasilkan nilai akurasi keseluruhan sebesar 94.52% dengan nilai koefisien kappa sebesar 0.97. Uji korelasi statistik dari persentase tutupan kanopi mangrove antara nilai NDVI dan data lapang menghasilkan nilai koefisien korelasi (r) yaitu 0.882 serta nilai koefisien determinasi (R2) yaitu 0.778., The condition of the mangrove ecosystem had declined in Mundupesisir Village, Mundu District, Cirebon Regency, West Java due to anthropological activities. This raised the urgency of monitoring the mangrove ecosystem so that damage did not worsen. This research aimed to map the distribution, density, and extent of mangroves in Mundupesisir Village using Sentinel-2A imagery. There were 2 algorithms used, namely the Mangrove Vegetation Index (MVI) algorithm and the Normalized Difference Vegetation Index (NDVI). The MVI algorithm was used to differentiate mangrove and non-mangrove vegetation with a threshold value of 2.374–19.409. The NDVI algorithm was used to map the distribution of mangrove density. Classification using the maximum likelihood method produced 3 classes of mangrove density with a total area of 23.07 hectares. These density classes consisted of dense (21.31 ha), medium (0.67 ha), and sparse (1.07 ha). The accuracy test using the confusion matrix method for mangrove density resulted in an overall accuracy value of 94.52% with a kappa coefficient value of 0.97. The statistical correlation test of the percentage of mangrove canopy cover between NDVI values and field data produced a correlation coefficient (r) value of 0.882 and a coefficient of determination (R2) value of 0.778.
Keyword: NDVI, MVI, Threshold, Cirebon Coast, Sentinel-2A

Judul: Sintesis Flavon dari Fenol dan Benzoil Klorida
Abstrak: Flavone is a class of flavonoid, commonly found in plants with wide bioactivity spectrum. A widely used flavone synthesis route is through acidcatalyzed oxidative cyclization of β-diketone. In this study, unsubstituted flavone had been synthesized via 5-step from phenol, with 22% yield and successfully increased the yield of previous study on Fries rearrangement of phenyl acetate and benzoylation of o-HAP steps. Phenol was acetylated resulting 93% phenyl acetate. AlCl3-catalyzed Fries rearrangement in 1.5 hour and at 120 °C converted phenyl acetate into o-hydroxyacetophenone (o-HAP) with 40% yield. AlCl3 as catalyst produced o-HAP with higher and reproducible yield compared with BF3·Et2O and ZnCl2. Benzoylation of o-HAP followed by Baker-Venkataraman rearrangement of the ester product using KOH in dried pyridine produced β-diketone 1-(2- hydroxyphenyl)-3-phenylpropane-1,3-dione. The yield of ester and β-diketone were 71% and 85%, respectively. Finally, oxidative cyclization of β-diketone with sulphuric acid as catalyst produced 99% of flavone. The flavone product had been characterized spectroscopically and its melting point as well.
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