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: Analysis of Changes in Mangrove Forest Density Levels Using SPOT 6 Image Indices in Tambak Sawah Luhur, Banten
Abstrak: Pembangunan di wilayah pesisir mengakibatkan degradasi lingkungan dan terancamnya kelestarian sumber daya alam pesisir khususnya hutan mangrove. Penelitian ini bertujuan mengalanisis tingkat kerapatan tutupan tajuk di lapang dan perubahan tingkat kerapatan hutan mangrove. Analisis tutupan lahan hutan mangrove menggunakan metode klasifikasi digital maximum likelihood dan visual, analisis kerapatan menggunakan indeks vegetasi citra SPOT 6 tahun 2016, 2019, dan 2022. Nilai persentase tutupan tajuk dan LAI di lapangan menggunakan metode hemispherical photography. Nilai ini digunakan untuk uji akurasi tingkat kerapatan hutan mangrove. Uji akurasi menunjukan hasil overall accuracy sebesar 83,33% pada NDVI dan SAVI. Indeks NDVI digunakan pada analisis perubahan luas tingkat kerapatan hutan mangrove tahun 2016-2019-2022, perubahan tingkat kerapatan sedang menjadi rapat seluas 4,327 ha (29%). Tahun 2019-2022, terjadi penurunan luas pada tingkat kerapatan rapat menjadi sedang yaitu seluas 6,471 ha (45%). Tahun 2016-2022 seluas 3,754 ha (26%) terjadi perubahan tingkat kerapatan jarang menjadi sedang., Coastal development leads to environmental degradation and threatens the preservation of coastal natural resources, particularly mangrove forests. This study aims to analyze the canopy cover density in the field and changes in mangrove forest density levels. The analysis of mangrove forest land cover employs digital classification methods, specifically maximum likelihood and visual analysis. Density analysis utilizes vegetation indices from SPOT 6 imagery for the years 2016, 2019, and 2022. The percentage values of canopy cover and Leaf Area Index (LAI) in the field are determined using the hemispherical photography method. These values are used to test the accuracy of mangrove forest density levels.The accuracy test results show an overall accuracy of 83.33% for both NDVI and SAVI indices. The NDVI index is used in analyzing changes in the extent of mangrove forest density from 2016 to 2019 to 2022, with a transformation from moderate to dense density levels covering an area of 4.327 ha (29%). From 2019 to 2022, there is a decrease in the extent of dense density areas, transforming into moderate density levels, covering an area of 6.471 ha (45%). Additionally, from 2016 to 2022, a significant change occurs, with an area of 3.754 ha (26%) transitioning from sparse to moderate density levels.
Keyword: density, hemispherical photography, index algorithms, mangrove

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.
Keyword: