Judul: Pixel-Based Study of Mangrove Land Cover and Shoreline Change Using Multi-Spectral Imagery in Maumere, Flores, East Nusa Tenggara.
Abstrak: Degradasi lahan mangrove menyebabkan perubahan pada garis pantai. Penelitian ini bertujuan untuk mengetahui pengaruh perubahan tutupan lahan mangrove pada garis pantai tahun 1990-2019 menggunakan citra landsat 1990, 2004, 2019 mengunakan klasifikasi Supervised Classification dan Metode DSAS digunakan untuk menghitung statistik laju perubahan garis pantai dan memetakan tutupan lahan di kawasan mangrove berbasis piksel menggunakan algoritma SVM dan Random Forest menggunakan citra sentinel 2A tahun 2020. Selanjutnya penelitian ini menganalisis perubahan tutupan lahan mangrove serta menganalisis hubungan antara tutupan kanopi mangrove dengan nilai NDVI dari citra satelit. Hasil penelitian menunjukan adanya degradasi mangrove 60,84 Ha periode waktu 1990-2004 dan mengalami penambahan 2,43 Ha, akibatnya dapat dilihat adanya Abrasi di daerah degradasi mangrove dengan nilai tertinggi -487.54m dan nilai akresi tertinggi 307.45m di daerah yang masih terjaga ekosistem mangrovenya. Hasil klasifikasi berbasis piksel menggunakan SVM diperoleh overall accuracy sebesar 90% (Kappa=.0.89) sedangkan Random Forest menghasilakn 88.13% (Kappa=0.87). hasil penelitian ini menunjukan bahwa algoritma SVM dapat menjadi pilihan menjanjikan untuk pemetaan mangrove. Luas mangrove Talibura menggunakan SVM adalah 234.51 Ha sedangkan Random Forest sebesar 193.95 Ha. Hubungan tutupan Kanopi dan nilai NDVI tinggi (r= 0,86) dan koefien determinasi sebesar r²=0.75 yang berarti tutupan kanopi mangrove berpengaruh terhadap NDVI sedangkan sisanya dipengaruhi oleh variable lainnya.
Keyword: Keywords: Classification, Mangrove, DSAS, SVM, Random Forest

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: Pemurnian dan karakterisasi protein inhibitor RNA helikase virus hepatitis C
Abstrak: Hepatitis C virus (HCV) infection is the second most common chronic viral infection in the world with global prevalence. This infection is contribution to chronic hepatitis and liver cirrhosis, often leading to hepatocellular carcinoma. There is no effective drug and vaccine available against HCV. The current standard treatment, a combination of pegylated interferon-α with ribavirin, is limited by its suboptimal response rate in a significant patient population, side effects, and affordability. Therefore, development of effective drug is needed. One approach to find out the candidate of antiviral drug is to discover the inhibitor of enzyme that essential for virus replication, such as RNA helicase. Streptomyces chartreusis 5-095 produce the inhibitor of HCV RNA helicase. The aim of this study was to purify the protein inhibitor which has inhibition activity against ATPase activity of RNA helicase HCV from S. chartreusis 5-095. The supernatant of culture S. chartreusis 5-095 exhibited high inhibiton activity against ATPase activity of RNA helicase HCV (approximately 72%) at 10 days of incubation. The extracellular protein inhibitor was partially purified by procedures of precipitation with ammonium sulfate to 65% saturation and gel filtration (Sephadex G50) using methanol water solution (4:6) as an eluen. The purity of protein inhibitor was monitored by SDS PAGE. The protein inhibitor showed a relative molecular mass were estimated to be 14 kDa and increased the purity 23,08 fold than those of the crude protein. The specific activity and IC50 after purification were 13,1338 U/mg and 0,0767 mg/mL, respectively. The activity of purified protein inhibitor showed its stability over pH range from 5-8 and optimum at pH 7,4. The inhibition activity showed its stability up to 70% at temperature 100 oC. The purified protein inhibitor relatively stable its activity at storage in the range of -20 oC to room temperature for 35 days.
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