Judul: Distribusi Lamun dan Mangrove menggunakan Citra Satelit Worldview-2 di Gugus Pulau Pari, Kepulauan Seribu
Abstrak: Teknologi satelit penginderaan jauh mempunyai kemampuan untuk mengidentifikasi dan memantau sumberdaya alam dan lingkungan wilayah pesisir. Tujuan penelitian ini adalah mengetahui distribusi lamun dan mangrove menggunakan citra Satelit WorldView-2 di Gugus Pulau Pari, Kepulauan Seribu. Pengolahan citra menggunakan algoritma NDVI untuk mendeteksi vegetasi lamun dan mangrove, yang menghasilkan nilai NDVI dari -0,987 sampai 0,936. Survei lapang di padang lamun menggunakan transek 1 m x 1 m yang diletakkan secara acak, sedangkan untuk mangrove menggunakan transek 10 m x 10 m. Jenis lamun yang ditemukan adalah Cymodocea rotundata, Enhalus acoroides, dan Thalassia hemprichii, sedangkan jenis mangrove yang ditemukan adalah Rhizophora mucronata. Di Pulau Karang Kudus, Pulau Biawak, dan Pulau Pari jenis lamun yang dominan adalah Enhalus acoroides, sedangkan di Pulau Burung jenis lamun yang dominan adalah Thalassia hemprichii. Kerapatan rata-rata mangrove di Pulau Biawak adalah 13 ind/100 m2 dan Pulau Burung memiliki Rhizophora mucronata dengan kerapatan rata-rata 43 ind/100 m2. Rhizophora mucronata di Pulau Pari memiliki kerapatan rata-rata 22 ind/100 m2. Hasil klasifikasi citra WorldView-2 menunjukkan luas lahan untuk lamun sebesar 324.200 m2, sedangkan untuk mangrove jarang adalah 12.500 m2, mangrove sedang sebesar 32.700 m2 dan mangrove lebat sebesar 47.800 m2., Satellite remote sensing technology has the ability to identify and monitor natural resources and environment in coastal areas. The purpose of this research was to determine the distribution of seagrasses and mangroves using WorldView- 2 imagery in Pari Island, Kepulauan Seribu. NDVI image processing algorithm for detecting seagrasses and mangroves vegetation was applied, resulting in NDVI values of -0.987 to 0.936. Groundtruth survey on seagrasses was conducted haphazardly using transect plot of 1 m x 1 m, while for mangroves was 10 m x 10 m. Observed seagrass species were Cymodocea rotundata, Enhalus acoroides, and Thalassia hemprichii, while mangrove was Rhizophora mucronata. Karang Kudus Island, Biawak Island and Pari Island had dominant seagrass species of Enhalus acoroides, while in Burung Island was dominated by Thalassia hemprichii. Average mangroves density in Biawak Island was 13 ind/100 m2 and Burung Island has Rhizophora mucronata with average density of 43 ind/100 m2. Rhizophora mucronata in Pari Island had an average density was 22 ind/100 m2. Classification results of WorldView-2 showed the extent area for seagrasses was 324.200 m2, while for sparse mangrove was 12.500 m2, medium 32.700 m2 and dense 47.800 m2.
Keyword: penginderaan jauh, distribusi, lamun, lamun, Pulau Pari

Judul: Mapping Mangrove Distribution Using Remote Sensing Technology in Harapan, Kelapa, and Pamegaran Islands, Kepulauan Seribu National Park
Abstrak: Keberadaan ekosistem mangrove semakin terancam akibat pesatnya pembangunan destinasi wisata dan bertambahnya jumlah penduduk di Pulau Harapan, Kelapa, dan Pamegaran sehingga perlu dilakukan pemantauan ekosistem mangrove. Tujuan penelitian untuk memetakan sebaran mangrove menggunakan teknologi penginderaan jauh di Pulau Harapan, Kelapa, dan Pamegaran. Metode klasifikasi maximum likelihood digunakan untuk mengklasifikasikan vegetasi mangrove dan non mangrove. Normalized Difference Vegetation Index (NDVI) merupakan algoritma untuk menduga indeks vegetasi dari citra satelit. Klasifikasi Citra Sentinel-2A menghasilkan 3 kelas kerapatan mangrove yakni kelas kerapatan rapat, sedang, dan jarang, dengan kelas dominan adalah kelas kerapatan rapat. Luas total mangrove di Pulau Pamegaran pada tahun 2015 sebesar 1,81 ha dan luas total mangrove di tahun 2021 sebesar 2,97 ha. Luas sebaran mangrove di Pulau Harapan dan Kelapa pada tahun 2015 sebesar 4,1 ha dan pada tahun 2021 sebesar 6,56 ha. Hasil uji akurasi sebaran kerapatan mangrove menggunakan confusion matrix pada klasifikasi citra dengan survey lapang menghasilkan akurasi sebesar 82,95%., The existence of mangrove ecosystems is increasingly threatened due to the rapid development of tourist destinations and the increasing number of residents in Harapan, Kelapa, and Pamegaran islands so that monitoring of mangrove ecosystems is necessary. The purpose of the research to map the distribution of mangroves using remote sensing technology in Harapan, Kelapa, and Pamegaran Islands. The maximum likelihood classification method is used to classify mangrove and non-mangrove vegetation. Normalized Difference Vegetation Index (NDVI) is an algorithm for guessing vegetation indexes from satellite imagery. Sentinel-2A image classification produces 3 classes of mangrove density, namely tight, medium, and rare density classes, with the dominant class being the tight density class. The total mangrove area on Pamegaran Island in 2015 amounted to 1,81 ha and the total mangrove area in 2021 amounted to 2,97 ha. The area of mangrove distribution in Harapan and Kelapa Island in 2015 amounted to 4,1 ha and in 2021 amounted to 6,56 ha. Mangrove density distribution accuracy test results using confusion matrix in image classification with field survey resulting in accuracy of 82,95%.
Keyword: Density, Mangrove, NDVI, Remote sensing, 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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