Judul: Modeling The Dependency of Stock Index Before and During the Covid-19 Pandemic
Abstrak: Pandemi Covid-19 merupakan peristiwa ekstrem yang saat ini terjadi di dunia. Pandemi Covid-19 menyebabkan lumpuhnya berbagai aktivitas perokonomian sehingga berdampak pada jatuhnya pasar saham. Oleh karena itu, pemodelan peristiwa ekstrem sangat penting untuk memprediksi kerugian besar yang terjadi di bidang keuangan. Copula nilai ekstrem merupakan metode yang tepat untuk menggambarkan hubungan kebergantungan antar aset saat peristiwa ekstrem. Dalam karya ilmiah ini, data yang digunakan adalah data imbal hasil indeks saham IHSG, STI, dan KLSE dari 1 Januari 2019 hingga 1 Oktober 2020. Data tersebut kemudian dikategorikan menjadi dua periode yaitu sebelum Covid-19 dan saat Covid-19. Dari data tersebut dibuat model ARMA-GARCH untuk mengatasi autokorelasi dan heteroskedastisitas. Kemudian ditentukan copula terbaik untuk data pada periode sebelum Covid-19 dan copula nilai ekstrem terbaik untuk data pada periode Covid-19. Copula t-Student dipilih sebagai copula terbaik untuk data pada periode sebelum Covid-19. Copula nilai ekstrem terbaik yang dipilih untuk ketiga indeks adalah copula Gumbel., The Covid-19 pandemic is an extreme event that is currently occurring in the world. The Covid-19 pandemic paralyzed various economic activities, resulting in the collapse of the stock market. Therefore, modeling of extreme events is very important to predict big losses in the financial sector. The extreme value copula is an appropriate method to measure the dependency between assets during extreme events. In this scientific work, the data used are return stock index of IHSG, STI, and KLSE from January 1, 2019 to October 1, 2020. Then, the data are categorized into two periods, before Covid-19 and during Covid-19. Form these data, an ARMA-GARCH model was created to overcome autocorrelation and heteroscedasticity. Then, the best copula was determined for data in the period before Covid-19 and the best extreme value copula for data in the Covid-19 period. The t-Student copula was chosen as the best copula for data in the period before Covid-19. The best extreme value copula chosen for the three indices is the Gumbel copula.
Keyword: Copula, Covid-19, Extreme Value Copula, Stock Index

Judul: Analysis of Optimal Stock Portfolio Formation during the Covid-19 pandemic with Multi-Index Models
Abstrak: Covid-19 berdampak ke sistem perekonomian, salah satunya dalam investasi saham. Risiko dalam investasi dapat diperkecil dengan membentuk portofolio. Karya ilmiah ini bertujuan mencari portofolio optimal dengan menggunakan model Multi Indeks. Model Multi Indeks menggunakan lebih dari satu indeks untuk menghitung expected return, sehingga dimungkinkan lebih akurat. Saham yang digunakan adalah saham yang tergabung di indeks LQ45 periode 1 Maret 2020 sampai 1 April 2021. Indeks pasar yang digunakan adalah IHSG, sedangkan indeks non-pasar adalah Dow Jones Industrial Average dan Hang Seng. Berdasarkan hasil penghitungan, portofolio optimal dibentuk dari 96.196498% saham TOWR dan 3.803502% ACES memiliki expected return harian sebesar 0.09047297% dengan risiko sebesar 2.52761%., Covid-19 has effect on the economic system, one of which is stock investment. The risk in investing can be minimized by forming a portfolio. The aim of this study is to determine the optimal portfolio using the Multi Index model. The Multi Index Model uses more than one index to calculate the expected return, so it is possible to be more accurate. The stocks used are stocks that are members of the LQ45 index for the period March 1, 2020 to April 11, 2021. The market index used is the IHSG, while the non-market indexes are the Dow Jones Industrial Avarage and the Hang Seng. Based on the calculation results, the optimal portfolio is formed from 96.196498% of TOWR stocks and 3.803502% of ACES which has an estimated daily return of 0.09047297% with a risk of 2.52761%.
Keyword: Covid-19, multi index model, portfolio

Judul: Membran Selulosa Berbahan Dasar Kulit Buah Nanas sebagai Adsorben Zat Warna Tekstil Biru Metilena
Abstrak: Treatment of various fruit pineapple in daily life created a problem of the environment, such as build up of peel waste. The waste could be transformed further to microbial cellulose (nata de pina) by using microorganisms Acetobacter xylinum. The application of microbial cellulose produced flux of 4.72-65.56 L/m2.h. The rejection membrane of methylene blue was 90 - 98 %, meaning that the membrane was able to adsorb methylene blue. Based on analysis using Fourier transform infrared and scanning electrone microscope the membrane composed of cellulose, with the type of asymmetry, and has pore size 20-50 nm as ultrafiltration membrane.
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