Judul: The Application of DNA Barcoding and DNA Metabarcoding for Marine Sponges Identification in Dampier Strait
Abstrak: Identifikasi spesies dapat dilakukan dengan berbagai metode diantaranya adalah dengan pengamatan morfologi dan pendekatan molekuler. Sifat plastisitas dari morfologi spons menyebabkan biota ini menantang untuk diidentifikasi. Upaya identifikasi dengan pendekatan molekuler dapat menjadi salah satu alternatif dalam kajian spons. Penelitian ini berujuan untuk mengidentifikasi spons dari sampel yang tidak utuh dengan pendekatan DNA barcoding dan DNA metabarcoding. Sampel spons yang diambil adalah sampel dengan tampak morfologi luar yang berbeda. Identifikasi dengan pendekatan molekuler dimulai dari ekstraksi DNA spons dan dilanjutkan dengan amplifikasi DNA. Analisis DNA barcoding menggunakan primer LCO 1490 dan HCO 2198, sedangkan analisis DNA metabarcoding menggunakan primer mlCOIlintf dan dgHCO2198 yang menargetkan gen Cytochrome Oxidase Subunit I (COI). Produk PCR kemudian dielektroforesis dan kualitas pita DNA yang baik akan dilanjutkan pada tahap sekuensing. Analisis genetik dengan metode DNA barcoding mendeteksi 4 jenis yaitu Halichondria sp., Stylissa carteri, Xestospongia deweerdtae, dan Theonella sp. dari 5 sampel yang teramplifikasi. Analisis DNA metabarcoding mendeteksi sebanyak 138 Operational Taxonomic Units (OTUs) dan 65.884 reads atau sekuen yang terdiri dari tiga kelompok yakni kelompok eukariot, kelompok bakteri, dan kelompok yang tidak teridentifikasi secara taksonomi (unassigned). Sampel spons pada penelitian ini dapat diidentifikasi dengan pendekatan DNA barcoding dan DNA metabarcoding. Penggunaan primer yang berbeda menyebabkan adanya perbedaan biota yang terdeteksi. Identifikasi spons dengan metode DNA barcoding menghasilkan taksonomi hingga tingkat spesies. Penggunaan metode DNA metabarcoding dapat mendeteksi tujuh genus spons serta memungkinkan deteksi spons jenis lain yang tidak terdeteksi dengan DNA barcoding. Genus spons yang terdeteksi pada analisis ini menggunakan metode molekuler diantaranya genus Agelas, Paratetilla, Pseudoceratina, Haliclona, Theonella, Halichondria, Xestospongia dan dua spesies diantaranya Xestospongia deweerdtae dan Stylissa carteri. Penerapan kedua metode ini juga sama-sama mendeteksi DNA non-target atau DNA selain spons. Rekomendasi untuk penelitian selanjutnya yakni preservasi yang lebih baik, dan penggunaan primer yang lebih spesifik.
Keyword: DNA Barcoding, DNA Metabarcoding, Porifera

Judul: Identification of Sponge Species Based on Morphology and Genetics in Raja Ampat, West Papua
Abstrak: Invertebrata laut termasuk kelompok hewan tidak bertulang belakang yang berperan dalam menjaga kestabilan ekosistem laut. Banyak spesies invertebrata laut yang belum teridentifikasi, salah satunya biota spons. Keberadaan spons tidak banyak diapresiasi, dipelajari dan diteliti dengan baik dibandingkan dengan biota laut lainnya. Beberapa penelitian terkait spons paling banyak dilakukan di wilayah Jawa dan Sulawesi. Penelitian terkait genetik dan tipe spikula tidak banyak dilakukan di Perairan Indonesia. Kesulitan identifikasi morfologi dan taksonomi menjadi salah satu faktor minimnya informasi terkait data spons. Tujuan penelitian ini yaitu mengetahui jenis-jenis spons yang ada di perairan Raja Ampat berdasarkan tipe spikula dan genetik. Identifikasi spesies berdasarkan genetik dilakukan dengan BLAST (Basic Local Alignment Search Tool) pada Genbank di NCBI (National Centre For Biotechnology Information) menggunakan data sekuen yang diperoleh dari sampel setelah melalui tahapan ekstraksi, PCR, elektroforesis, dan sekuensing. Rekonstruksi pohon filogeni dibuat menggunakan model Kimura 2-parameter dengan metode Neighbour Joining dan Maximum Parsimony. Identifikasi bentuk spikula spons dilakukan dengan pengamatan preparat menggunakan mikroskop majemuk. Berdasarkan analisis laboratorium dari 22 sampel ditemukan 5 sampel terdeteksi sebagai spesies spons Halichondria sp., Stylissa carteri, Xestospongia deweerdtae, dan Theonella sp. Rekonstruksi pohon filogeni menghasilkan empat clade besar. Bentuk tipe spikula yang teramati terdiri dari spikula monoaxon dan tetraxon., Marine invertebrates are a group of invertebrate animals that play a role in maintaining the stability of marine ecosystems. Many marine invertebrate species have not been identified, one of which is the sponge. The existence of sponges is not much appreciated, studied and well researched compared to other marine biota. Most research related to sponges has been carried out in Java and Sulawesi. Research related to genetics and spicule types is not much carried out in Indonesian. The difficulty of identifying morphology and taxonomy is one of the reasons for the lack of information related to sponge data. The purpose of this study was to determine the types of sponges in Raja Ampat based on the type of spicules and genetics. Genetic identification of species was carried out using BLAST (Basic Local Alignment Search Tool) on Genbank at NCBI (National Center For Biotechnology Information) using sequence data obtained from samples after going through the stages of extraction, PCR, electrophoresis and sequencing. Phylogenetic tree reconstruction was made using the Kimura-2 parameter model with the Neighbor Joining and Maximum Parsimony methods. Identification of the shape of sponge spicules was carried out by observing the preparations using a compound microscope. Based on laboratory analysis of 22 samples, it was found that 5 samples were detected as Halichondria sp., Stylissa carteri, Xestospongia deweerdtae, and Theonella sp. Phylogenetic tree reconstruction resulted in four large clades. The types of spicules observed consisted of monoaxon and tetraxon spicules.
Keyword: DNA barcoding, genetic, spicule, sponge

Judul: The Effects of Variance of Interest rate to Variance of Annuity Future Values
Abstrak: Time value of money is a concept that refers to the difference of the value of money due to time difference. The value of money for present time would not be the same as the value of money in the future. The value of money for present time is called as Present Value (PV) of the money and the value of money for future time is called Future Value (FV) of the money. Determination the value of money, for present and future time, depends on the time and rate of return. The value of money is determined by several factors such as inflation, fluctuation of interest rates, and government policy in securities and taxation. Due to fluctuation of the value of money we need a FV formulation, it is useful for knowing whether an investment can be profitable or not, and this information is useful also in budget analysis. Annuity is defined as a series of payments made for a specific period. The payment, fixed or varied, can be made at the beginning or at the end of the period. Annuity paid at the beginning of the period is called annuity-due and annuity paid at the end of the period is called immediate annuity-certain. The accumulated value of the annuity after few years later is called as a final value or a future value. Burnecki et al. (2003) have discussed about the FV of a fixed-rate annuity in which payments are made according to the arithmetic or geometric series. They have also examined FV for annuities in which payments are made according to arithmetic or geometric series with random rates of interest. This paper examines FV for annuity-due in which payments are made according to arithmetic or geometric series with interest rates as a random variable, which is normal distribution ,  . Future value formula is expressed in recursive form. FV for annuity-due which payments are made according to the arithmetic or geometric series with random rates of interest is calculated by theoretical way and simulation way. The random rates of interest is denoted as k k i  i  , where k i an independent random variable; i is a constant and k  is a random variable which has normal distribution ,  . By using the determined parameters, a sequence of random rates of interest are generated for theoretical calculation. Meanwhile for the simulation, the random rates of interest is generated 1000 times for the simulation. The generated data give mean value, variance, and standard deviation. Moreover, error of mean value, variance, and standard deviation from the theoretical and simulation results are calculated. Error calculation uses Symmetric Mean Absolute Percentage Error (SMAPE). The smaller the value of SMAPE is the more accurate the simulation. The interest rate variances are varied from 0.000036 to 0.0001 to study the relationship between variance of rates of interest and variance of future value. The theoretical and simulation results show that when the variance of random rates of interest increases, then the variance of FV increases linearly. FV of the annuity-due in
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