Judul: Modeling Dependence between Agricultural Commodities with The C-Vine Copula Method
Abstrak: Ketidakpastian terhadap produksi komoditas pertanian mengakibatkan harga komoditas pertanian menjadi sangat fluktuatif. Harga komoditas pertanian pada pasar pertanian sangat jarang mengikuti sebaran normal dan antara komoditas dengan komoditas lain sering kali saling memengaruhi. Oleh karena itu, digunakan copula untuk menangkap hubungan kebergantungan antar harga komoditas pertanian. Dalam karya ilmiah ini digunakan data harga harian komoditas pertanian CPO, Minyak Kelapa, dan Olein dari tanggal 1 Januari 2018 hingga 1 September 2020. Model ARMA-GARCH dibuat untuk mengatasi masalah autokorelasi dan heteroskedastisitas. Kemudian, diukur koefisien-koefisien korelasi antardata dengan menggunakan korelasi rank. Selanjutnya dicari copula terbaik, dan didapat copula-t merupakan copula terbaik untuk semua pasangan komoditas. Kemudian, dilakukan konstruksi struktur tree dari model C-Vine Copula. Model tersebut merepresentasikan kebergantungan antarharga komoditas pertanian melalui fungsi copula dua peubah. Fungsi-fungsi copula yang sesuai adalah copula-t dan copula Frank., Uncertainty over the production of agricultural commodities has resulted in very volatile agricultural commodity prices. Prices of agricultural commodities in the agricultural market rarely follow a normal distribution and between commodities and other commodities often influence each other. Therefore, a copula is used to capture the dependency relationship between agricultural commodity prices. In this scientific paper, daily price data on agricultural commodities of CPO, Coconut Oil and Olein from January 1, 2018 to September 1, 2020 are used. The ARMA-GARCH model is made to overcome the problems of autocorrelation and heteroscedasticity. Then, the correlation coefficients between data are measured using rank correlation. Next, the best copula is searched. The t-copula is the best copula for all commodity pairs. Then, the tree structure construction is carried out from the C-Vine Copula model. The model represents the dependence of agricultural commodity prices through the copula function of two variables. The corresponding copula functions are the t-copula and Frank’s copula.
Keyword: ARMA, C-Vine Copula, Copula, GARCH

Judul: Pembandingan  Metode Copula dan D-Vine Copula dalam Estimasi Tail Value at Risk pada  Komoditas Pertanian
Abstrak: Risiko adalah salah satu hal yang perlu dihitung investor untuk mengetahui perkiraan kerugian yang harus ditanggung. Salah satu alat ukur yang digunakan untuk menghitung risiko portofolio adalah Value at Risk (VaR). Namun, VaR memiliki kekurangan dalam hal subadditivity sehingga muncul konsep Tail Value at Risk (TVaR) yang memenuhi sifat koherensi ukuran risiko. Dalam penelitian ini, dilakukan penghitungan nilai VaR dan TVaR menggunakan data imbal hasil Crude Palm Oil (CPO), minyak kelapa, dan olein. Model ARMA-GARCH digunakan untuk mengatasi autokorelasi dan heteroskedastisitas pada komoditas-komoditas tersebut. VaR dan TVaR diukur dari portofolio model copula dan D-Vine copula. Fungsi copula yang terpilih yaitu copula-t dan copula Gauss. Setelah didapat sebaran bersama kemudian dilakukan pendugaan nilai VaR dan TVaR dengan Simulasi Monte Carlo yang selanjutnya digunakan backtesting untuk menguji kevalidan nilainya. Dengan memberikan bobot yang sama, pada tingkat kepercayaan 99% dengan copula diperoleh nilai estimasi TVaR sebesar 7.952167% dan dengan D-Vine copula diperoleh nilai estimasi TVaR sebesar 7.050056%., Risk is one of the things that investors need to calculate to find out the estimated losses that must be borne. One of the measuring tools used to calculate portfolio risk is Value at Risk (VaR). However, VaR has deficiency in subadditivity property, so the concept of Tail Value at Risk (TVaR) appears which satisfies the coherence property of risk measures. In this study, the VaR and TVaR values were calculated using the return data of Crude Palm Oil (CPO), coconut oil, and olein. The ARMA-GARCH model is used to overcome autocorrelation and heteroscedasticity effects in these commodities. VaR and TVaR were measured from the copula and D-Vine copula model portfolios. The selected copula functions are t-copula and Gaussian copula. After getting the joint distribution, VaR and TVaR values were estimated with Monte Carlo Simulation and then backtesting is used to test the validity of the values. By giving the same weight to each commodity, at a confidence level of 99% when using copula, the estimated TVaR value is 7.952167%, and using the D-Vine copula the TVaR estimate is 7.500056%.
Keyword: Tail Value at Risk, ARMA, GARCH, Copula, Drawable Vine Copula, Backtesting

Judul: Photosensor producing based on ferroelectric material of Ba0,5Sr0,5TiO3 doped by Ferrium Oxide (Fe2O3) on a P-Type Silicon Substate Si (100) applied as a digital camera with a single pixel image sensor
Abstrak: Thin film Ba0,5Sr0,5TiO3 (BST) doped with Fe2O3 was grown on p-type silicon substrate (100) using chemical solution deposition (CSD). It used the solvent 2-methoxyethanol with annealing temperature of 850°C and the doping treatment Fe2O3 of 2.5, 5, 7.5, 10 % of the mass formed BST. Pure BST had the highest absorption of 600 nm of light wavelength. Additions Fe2O3 moves highest absorption in the range of 560 nm. Fe2O3 addition was strengthening thin film sensitivity to the effects of light. In general, doping Fe2O3 10% was result the best absorbance and current-voltage of BST thin film. Electrical properties of thin films BST include dielectric, photoconductivity, and dissipation energy. Based on the current-voltage (I-V) analysis, pure BST and doped BST showed photodiode properties. Dielectric values obtained in the range from 23.32 to 243. Based on electrical conductivity data and energy dissipation, BST thin films have shown photodiode characteristics and are therefore suitable as light sensors. The image sensor in a digital camera is also a light sensor. This BST thin film has been scientifically proven to be a light sensor and also it can be applied as an image sensor. This is a novelty image sensor based on thin film Ba0.5Sr0.5TiO3.
Keyword: barium strontium titanate, thin film, photodiode, image sensor, digital camera