Judul: Stochastic Modeling of Daily Clearing Transactions and Its Prefund Clearing
Abstrak: Bank Indonesia-Real Time Gross Settlement (BI-RTGS) system is very important in payment transactions. It has huge value and potential systemic risk due to the total value of the transactions. In 2019, the amount of daily RTGS transactions reached 3.5% of Indonesia's Gross Domestic Product. Since the new regulation on the clearing system was issued, BI has set a clearing prefund that is considered high for middle down class bank, it has an impact on banking management because not all bank has the ability to provide the prefund so that bank has to sacrifice potential profits from available cash funds. Meanwhile, there are idle funds that is caused by determination based on nonoutlier data with the lowest daily negative netting from the past year. It is necessary to build stochastic modeling about the characteristics of the clearing system to obtain an optimal prefund which has 1% and/or 5% settlement failure also the lowest potential loss prefund. Forecasting by Seasonal ARIMA helps this research in determining the prefund for the next year. The inventory model is considered to be similar to the clearing model with several changes and assumptions. The results of the stochastic process of daily clearing transactions show that the prefund value with the lowest potential loss is around the average daily clearing value and the prefund with a settlement failure of 1% and 5% has a lower value than the prefund set by BI. Keywords: clearing, modeling, prefund, stochastic, transaction., Kehadiran sistem Bank Indonesia-Real Time Gross Settlement (BI-RTGS) sangat penting dalam transaksi pembayaran yang bernilai besar namun berpotensi risiko sistemik dikarenakan nilai total transaksinya. Di tahun 2019, total transaksi RTGS harian mencapai 3,5% dari Produk Domestik Bruto Indonesia. Sejak regulasi baru sistem kliring diterbitkan, BI menetapkan prefund kliring yang dianggap tinggi untuk bank kelas menengah ke bawah, hal ini berdampak pada manajemen perbankan karena tidak semua bank memiliki kemampuan untuk menyediakan prefund tersebut sehingga bank harus mengorbankan potensi keuntungan dari dana tunai tersedia. Sedangkan terdapat dana idle yang disebabkan penentuan berdasarkan data nonoutlier dengan netting negatif harian terendah selama setahun terakhir. Perlu pemodelan stokastik terhadap karakteristik sistem transaksi kliring untuk memperoleh prefund optimal yang memiliki kegagalan setelmen 1% dan/atau 5% serta prefund dengan potensi kerugian terendah. Peramalan data dengan menggunakan Seasonal ARIMA membantu dalam menentukan prefund di tahun berikutnya. Model inventori dianggap mirip dengan model transaksi kliring dengan beberapa perubahan dan asumsi baru. Dari proses stokastik transaksi kliring harian menunjukkan bahwa nilai prefund dengan potensi terendah berada di sekitar rata-rata nilai transaksi kliring harian dan prefund dengan kegagalan setelmen 1% dan 5% memiliki nilai yang jauh lebih rendah dari prefund yang ditetapkan oleh BI.
Keyword: kliring, pemodelan, prefund, stokastik, transaksi

Judul: Determination of Benefit Reserves on Endowment Insurance with Full Preliminary Term Method and Stochastic Interest Rates Model
Abstrak: Premi dan cadangan manfaat asuransi dipengaruhi oleh suku bunga. Perubahan nilai suku bunga merupakan proses stokastik yang dapat diamati menggunakan model stokastik. Tujuan dari penelitian ini adalah menentukan premi bersih dan juga cadangan manfaat berdasarkan metode full preliminary term untuk asuransi jiwa dwiguna sepuluh tahun menggunakan suku bunga model stokastik. Data BI 7-day (Reverse) Repo Rate periode Mei 2016 hingga Oktober 2020 dimodelkan dengan model stokastik Cox, Ingersoll, Ross (CIR). Parameter model CIR diestimasi menggunakan metode regresi ordinary least square. Model CIR digunakan untuk membangkitkan data suku bunga baru yang selanjutnya digunakan untuk simulasi dengan iterasi seratus kali pada penghitungan premi bersih dan cadangan manfaat. Data premi bersih dan cadangan manfaat hasil dari simulasi selanjutnya disajikan dalam bentuk selang kepercayaan 95%. Hasil menunjukkan bahwa semakin tua peserta saat mendaftar asuransi maka semakin pendek selang kepercayaan 95% bagi premi bersih dan cadangan manfaat pada tahun-tahun tertentu., Premium and benefit reserves insurance are affected by interest rates. Changes in the value of interest rates are stochastic process that can be observed using a stochastic model. The purpose of this study is to determine net premium and also benefit reserves based on full preliminary term method for ten years endowment life insurance using a stochastic model of interest rate. BI 7-day (Reverse) Repo Rate data from May 2016 to October 2020 was modeled using the Cox, Ingersoll, Ross (CIR) stochastic model. The CIR model parameters were estimated using ordinary least square regression method. The CIR model is used to generate new interest rate data which is then used for simulation with one hundred times iteration in calculating net premium and benefit reserves. The data of net premium and benefit reserves from the simulation are presented in the form of a 95% confidence interval. The results show that the older participant registered for insurance, the shorter 95% confidence interval for the net premium and benefit reserves in certain years.
Keyword: benefit reserves, CIR model, confidence interval, insurance, premium

Judul: Enrichment of organic selenium, inorganic selenium and  vitamin E in quail products through its supplementation in the diet and its potency  of quail eggs as an ingredient in selenium-rich egg juice
Abstrak: This study was aimed to achieve an optimum level of combine organic selenium, inorganic selenium and vitamin E in obtaining the best production and reproduction as well as the highest level of selenium in quail eggs. This study was conducted from January to August 2008. Numbers of observed quails were 720 (360 females and 360 males). The treatments were applied when the quails were six weeks old. Nine treatment diets were: To (commercial diet), T1(0.46 ppm inorganic Se + 43.50 ppm vitamin E), T2 (0.46 ppm inorganic Se + 87.00 ppm vitamin E), T3 (0.92 ppm inorganic Se + 43.50 ppm vitamin E), T4 (0.92 ppm inorganic Se +87.00 ppm vitamin E), T5 (0.46 ppm organic Se + 43.50 ppm vitamin E), T6 (0.46 ppm organic Se + 87.00 ppm vitamin E), T7(0.92 ppm organic Se + 43.50 vitamin E) and T8(0.92 ppm organic Se + 87.00 ppm vitamin E).
Keyword: egg yolk, glutathione peroxidase ( GSH-Px), hedonic test, rank test