Judul: Keanekaragaman Selaginella di Jawa Barat.
Abstrak: Selaginella is a genus of ferns in the family Selaginellaceae. It is characterized by having small leaves and the spongarium on the tip of each branch. The society of West Java have been a long time used Selaginella as vegetable and dill, but the taxonomic information of Selaginella in West Java is still poorly known. The aim of this research was to describe the diversity of Selaginella in West Java. This research used 316 herbarium specimens of Selaginella collected by Plant Taxonomy Laboratory, Department Biology of Bogor Agricultural University and Herbarium Bogoriense Botanical, Research and Development Cibinong. From each specimen was observed the mophological characters, recorded the spread site, identified, then arranged the identification key. This study showed that 18 species found in West Java, namely S. aristata, S. biformis, S. ciliaris, S. frondosa, S. intermedia, S. involvens, S. mayeri, S. opaca, S. ornata, S. plana, S. remotifolia, S. rothertii, S. subalpina, S. subspinulosa, S. uncinata, S. willdenovii, S. zollingerian and Selaginella sp 1. Selaginella is able to live at altitudes ranging from 20 m above sea level (asl) to > 2500 m asl, with a variety of habitats including primary forest, in the rice fields, near the waterways, and in the open area. An identification key of Selaginella in West Java was provided in this paper.
Keyword: identification key, Selaginella, taxonomic, West Java.

Judul: Metabolomic Analysis of Selaginella spp. (Selaginellaceae) and its Potential as Medicinal Plants
Abstrak: Selaginella merupakan salah satu marga tumbuhan paku dari suku Selaginellaceae yang memiliki keragaman spesies yang tinggi di daerah tropis dan subtropis. Selaginella memiliki potensi dan manfaat yang cukup besar terutama dalam bidang kesehatan, khususnya dapat dimanfaatkan sebagai tumbuhan obat. Namun, informasi metabolit pada Selaginella spp. masih terbatas. Penelitian ini bertujuan menganalisis metabolit pada Selaginella spp. yang dapat dimanfaatkan sebagai obat dan dapat digunakan sebagai pembeda antar spesies. Metode penelitian yang dilakukan meliputi preparasi sampel, ekstraksi sampel, analisis kandungan metabolit dengan LC-MS/MS, dan analisis data. Analisis metabolomik meliputi identifikasi metabolit menggunakan perangkat lunak MZmine 3.1.0 beta, analisis profil metabolit, klaster heatmap, dan analisis gugus menggunakan MetaboAnalyst 5.0. Hasil analisis menunjukkan sebanyak 113 metabolit terdeteksi pada tiga spesies Selaginella yang diamati. Analisis gugus berdasarkan ciri metabolit mengelompokan seluruh individu menjadi 3 kelompok sesuai dengan spesiesnya. Metabolit Selaginella willdenowii lebih mirip Selaginella ornata dibandingkan dengan Selaginella plana. Beberapa senyawa yang terdeteksi memiliki manfaat penting dalam bidang pangan, kesehatan, dan kecantikan. Senyawa aloeresin a, naringin, rhoifolin, isoschaftoside, isovitexin 2''-oarabinoside, 4-vinylphenol, dan isofraxidin merupakan kandidat penanda kimia pada Selaginella plana. Senyawa velutin, aspalathin, 2-hydroxybenzaldehyde, gardenin a, catechol, dan n-(1,1-dimethyl-3-oxobutyl)acrylamide merupakan kandidat penanda kimia pada Selaginella ornata. Senyawa kapakahine b, dihydrojasmonic acid, linoleic acid, alantoic acid, menaquinone, dan nandrolone merupakan kandidat penanda kimia pada Selaginella willdenowii., Selaginella is a genus of Pteridophyta from the Selaginellaceae which has high diversity in tropical and subtropical areas. Selaginella has considerable potential and benefits, particularly it can be used as a medicinal plant. However, information on metabolites in Selaginella spp. is still limited. This study aimed to analyze the metabolite compounds in Selaginella spp. which can be used as medicine and as a biomarker to differentiate among species. The research methods included sample preparation, sample extraction, analysis of metabolite content by LC-MS/MS, and data analysis. The metabolomic analysis included the identification of metabolites using MZmine 3.1.0 beta software, analysis of metabolite profiles, and cluster analysis using MetaboAnalyst 5.0. The results of the analysis showed that as many as 113 different metabolites were detected in the three Selaginella species. Metabolite based cluster analysis grouped all individuals into 3 groups according to the species. Selaginella willdenowii metabolites are more similar to Selaginella ornata than Selaginella plana. Some of the metabolites detected have important benefits for food, health, and beauty. Aloeresin a, naringin, rhoifolin, isoschaftoside, isovitexin 2''-o-arabinoside, 4- vinylphenol, and isofraxidin compound are candidate chemical markers in Selaginella plana. Velutin, aspalathin, 2-hydroxybenzaldehyde, gardenin a, catechol and n-(1,1-dimethyl-3-oxobutyl)acrylamide compound are candidate chemical markers in Selaginella ornata. Kapakahine b, dihydrojasmonic acid, linoleic acid, alantoic acid, menaquinone, and nandrolone compound are candidate chemical markers in Selaginella willdenowii.
Keyword: cluster analysis, heatmap, LC-MS/MS, metabolite

Judul: Dynamical System of Hepatitis B in Three Groups with Vaccination
Abstrak: The aim of this study is to modify the hepatitis B transmission model in three age groups involving vaccination from the model conducted by Zhoe and Zhang.The method used is to analyze the stability of the fixed point and its basic reproduction number (R_0). Performed stability analysis and numerical simulation to see population dynamics. Next, a sensitivity analysis of the parameters was carried out to see its effect on R_0. From the analysis obtained two fixed points, namely non-endemic and endemic fixed points. Non-endemic fixed points are locally asymptotically stable if R_0 <1 Meanwhile, the endemic fixed point is locally asymptotically stable if R_0 > 1. Hepatitis vaccination affects the number of susceptible population, because the more successful the vaccination, the smaller the number of susceptible populations so that the smaller the population will be infected.
Keyword: Dynamic, Hepatitis B, Vaccine, Mathematical model