Judul: Potential of bacterial simbionts of seagrass as preventing marine Biofouling
Abstrak: Biofouling is defined as the attachment and growth of microorganisms (microbial fouling) and macroorganisms (macrofouling) on solid surface. Biofouling bacteria also result on surface of marine plant seagrass as symbiotic. Bacteria-seagrass association that occur on the surface have been known to produce secondary metabolites that have important ecological roles, including prevention from pathogen infection and fouling organisms. A research aimed at the bacterial symbionts of seagrass Enhalus acoroides, Thalassia hemprichii and Syringodium isoetifolium as defense marine biofouling was performed. Bacterial symbionts including endophytes and epiphytes were isolated from the seagrass. Marine biofilm-forming bacteria had been isolated from the fiber and wooden panels from the surrounding colonies. Epiphyte isolate found more than endophyte isolate, however more biological activity was found among endophyte compare to epiphyte against biofilm-forming bacteria. Bacterial endophyte inhibited more biofilm-forming bacteria than epiphyte. Extract endophytes and epiphytes bacteria also inhabited biofilm-forming bacteria. Field experimental of extract bacteria show that extract of two bacteria spesies cannot obtained fouling organisms identified as Virgibacillus genus and one identified as Bacillus genus. Bacterial symbionts of seagrass in this experiment show potential source as natural marine antifouling.
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Judul: Eksplorasi Bakteri Simbion Spons di Ekosistem Lamun
Abstrak: Sponge has been acknowledged for its ability to produce secondary metabolites compounds that have been explored for new source of marine natural product compounds. Unfortunately, information on sponge ecological interaction, especially concerning its secondary metabolite production and symbiotic organisms, are usually from observation and experimental researches in coral reefs ecosystem. Meanwhile, not many information has been gathered on sponge community and its ecological interaction in the seagrass ecosystem. Information on sponge community and its ecological interaction in seagrass ecosystem should be explored intensively, for seagrass vegetation could has different environmental condition due to seagrass species characterization that composing the ecosystem. Thus, vegetation characterization of seagrass will influence sponge community and its secondary metabolite, and also its interaction with symbiotic microbial (bacterial). This research wants to figure out several issues concerning sponge community in seagrass ecosystem. These issues are: will sponge species composition and association be different due to condition of seagrass vegetation in the ecosystem; is sponge species in seagrass ecosystem have the same potential concerning its antibacterial activity as in reefs area; how diverse the sponge bacterial symbiont and the potential of its secondary metabolite; and also how the ecological interaction between sponge and its symbiotic bacterial. This research was conducted in several stages. The first stage is field observation at seagrass ecosystem. The next stage was conducted as laboratory activities. Laboratory activities were conducted in several phases. The phase was an assay to test the antibacterial activity of sponges tissues on generally tested bacteria (Escherichia coli and Staphylococcus aureus) and marine bacteria isolates from surrounding water (Al1, Al2, Al3, Al4 and Al5). The aims of this activity were to screen potential sponge that having antibacterial activity, and isolating its symbiotic bacterial. Afterwards, the next phase was an assay to test the antagonistic activity of sponge symbiotic bacterial against marine-biofilm forming bacteria. Symbiotic bacterial with high antagonistic activity then analyzed for its species diversity, using molecular analysis of symbiotic bacterial DNA fingerprinting and identification. Field observation was done in two different seagrass meadow/bed in Pramuka Island, Seribu Islands, near Jakarta Bay, Indonesia, since September 2013 to Mei 2014. Laboratory assays activities were done in Marine Microbiology Laboratory and Marine Biosystematics and Biodiversity, Departement of Marine Science and Technology, Bogor Agricultural University (IPB). Antibacterial assay on sponge tissue was conducted since September 2013 to March 2014, whilst isolation on symbiotic bacterial and secondary metabolites assay were done from December 2013 to November 2015. Molecular analysis on bacterial symbionts diversity and identification were just done ons January to May 2016. Results of this research showed that sponge community in seagrass ecosystem was influenced by the density, morphological form and vegetation architectural of seagrass beds. Sponge will have more species number (higher diversity), with lower abundance in patchy seagrass bed. On the contrary, diversity of sponge will be lower, with higher individual number (abundance) in continuous seagrass bed, regarding higher protection mechanism from predatory activities in continuous bed. Overall, sponge community at both seagrass beds (Site 1 and 2) were dominated by Spirastrella sp. (Sp) and Agelas conifera sponges. Antibacterial assay showed that only
Keyword: asosiasi spons, anti biofilm, bakteri simbion, interaksi ekologis, lamun

Judul: Pemodelan Nilai Tukar Rupiah Terhadap US Dollar Menggunakan Deret Waktu Hidden Markov Satu Waktu Sebelumnya
Abstrak: Perubahan nilai tukar Rupiah terhadap US Dollar dapat terjadi kapan saja dalam suatu periode waktu yang panjang dan perubahan yang terjadi mungkin terjadi kembali di masa mendatang. Jika penyebab kejadiannya tidak diamati secara langsung dan membentuk rantai Markov maka perubahan nilai tukar Rupiah terhadap US Dollar dapat dimodelkan dengan deret waktu Hidden Markov. Model yang dibahas dalam karya ilmiah ini adalah model deret waktu Hidden Markov satu waktu sebelumnya di mana nilai tukar Rupiah saat ini selain bergantung pada nilai tukar Rupiah satu waktu sebelumnya, juga bergantung pada faktor penyebab saat ini dan satu waktu sebelumnya. Parameter model diduga menggunakan metode Maximum Likelihood dan perhitungannya digunakan algoritma iteratif Expectation Maximization (EM). Untuk mempermudah proses pendugaan parameter, proses komputasi numerik dilakukan dengan menggunakan software Mathematica 6. Setelah penduga parameter didapatkan maka dapat dihitung nilai tukar Rupiah terhadap US Dollar yang akan datang. Dari hasil yang diperoleh, model deret waktu Hidden Markov satu waktu sebelumnya dapat memodelkan perubahan nilai tukar Rupiah terhadap US Dollar dengan sangat baik. Ini dilihat dari nilai galat maksimum adalah 807,6963 (5,6773 %) dan nilai galat minimum adalah 0,2934 (0,0032 %).
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