Judul: Mapping the Extent and Density of Mangroves Using Sentinel 2A Image Classification in CMC Tiga Warna
Abstrak: Mangrove adalah tumbuhan pantai yang tumbuh di daerah pasang surut dan pantai berlumpur. Berfungsi sebagai zona penyangga dan melindungi garis pantai dari kerusakan akibat abrasi. Teknologi penginderaan jauh sangat tepat digunakan untuk pemantauan ekosistem mangrove di CMC Tiga Warna yang mengalami peningkatan belakangan ini. Tujuan dari penelitian ini adalah untuk mengetahui perubahan luasan dan kerapatan mangrove menggunakan Citra Sentinel-2A. Klasifikasi kerapatan citra menggunakan metode Normalized Difference Vegetation Index (NDVI) dan dilakukan pengambilan data lapang sebanyak 55 titik menggunakan metode Hemispherical photography. Hasil penelitian menunjukkan 3 kelas kerapatan mangrove yaitu kelas rapat dengan luasan sebesar 46,10 ha, kelas sedang 0,75 ha, dan kelas jarang 0,82 ha pada tahun 2015. Tahun 2023 luas mangrove untuk kelas rapat, sedang dan jarang masing-masing adalah 62,27 ha, 1,01 ha, dan 0,59 ha. Luas total hutan mangrove tahun 2015 sebesar 47,67 ha dan tahun 2023 sebesar 63,87 ha. Kerapatan mangrove di CMC Tiga Warna mengalami peningkatan selama 8 tahun terakhir pada kelas rapat dan sedang. Hal ini mengindikasikan program pengelolaan mangrove di lokasi ini dapat dikatakan berhasil., Mangroves are coastal plants that grow in tidal and muddy areas. They function as buffer zones and protect coastlines from abrasion damage. Remote sensing technology is highly suitable for monitoring the mangrove ecosystem in CMC Tiga Warna, which has experienced recent growth. The objective of this study is to determine changes in the extent and density of mangroves using Sentinel-2A imagery. The classification of density was conducted using the Normalized Difference Vegetation Index (NDVI) method, and field data collection is conducted at 55 points using the Hemispherical Photography. The research results show that there are 3 density classes of mangroves, namely dense class with an area of 46.10 ha, moderate class 0.75 ha, and sparse class 0.82 ha in 2015. In 2023, the area of mangroves for dense, moderate, and sparse classes respectively are 62.27 ha, 1.01 ha, and 0.59 ha. The total area of mangrove density in 2015 was 47.67 ha, while in 2023 it reached 63.87 ha. The mangrove density in CMC Tiga Warna has increased by 16.2 ha over the past 8 years for the dense and moderate classes. It indicates that the development program of mangrove in this location can be considered successful.
Keyword: CMC Tiga Warna, Kerapatan, Mangrove, NDVI, Sentinel 2A Satelit

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: The Dynamic of HIV Virus Infection as a Result of Protease Inhibitor Therapy.
Abstrak: Acquired immunodeficiency syndrome (AIDS) is defined as symptoms of deterioration human immune system caused by human immunodeficiency virus (HIV). The virus damages the leucocytes; therefore, once a person infected by the HIV, his/her immune system will be paralyzed and eventually will not be able to survive from any disease. HIV is transmitted in many ways, such as having unsafe sex, using unsterilized syringe, blood transfusion, and many more. So far, there has not been discovered yet a way or a medicine that can totally cure this disease. However, reverse transcriptase inhibitor therapy, protease inhibitor, or combination of those two can decline the growth of virus inside the body of the infected person. Therefore, the immune system will be enhanced back to normal phase. In this paper, will analyze the effect of protease inhibitor therapy on the dynamics of virus inside the blood with different value of effectiveness. There are two mathematical models of protease inhibitor therapy to consider, i.e. perfect and imperfect protease inhibitor. The perfect protease inhibitor therapy hinders the virus to grow well and not to infect healthy leucocytes. On the other hand, the imperfect one cannot completely detained the virus growth.
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