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All Journal Media Statistika Jurnal Ilmu Dasar Jurnal Gaussian Jurnal Kajian Akuntansi Euler : Jurnal Ilmiah Matematika, Sains dan Teknologi

Di Asih I Maruddani

Jurusan Statistika FSM UNDIP

Author-ID : 316727

Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Mathematics Other

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PENGGUNAAN SIMULASI MONTE CARLO UNTUK PENGUKURAN VALUE AT RISK ASET TUNGGAL DAN PORTOFOLIO DENGAN PENDEKATAN CAPITAL ASSET PRICING MODEL SEBAGAI PENENTU PORTOFOLIO OPTIMAL (Studi Kasus: Index Saham Kelompok SMinfra18) Pradana, Danang Chandra; Maruddani, Di Asih I; Yasin, Hasbi
Jurnal Gaussian Vol 4, No 4 (2015): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

In financial markets, a stock is a unit of account for various investments. It often means the stock of a corporation, but also used for collective investments such as mutual funds, limited partnerships, and real estate investment trusts. In this era, most investors establish a stock portfolio as one way to reduce the risk of loss or risk which may be obtained when investing in stocks. Formation of portfolio in this research, investors is used to calculate the weight of the investment using the Capital Asset Pricing Model (CAPM). Risks of investing often called Value at Risk (VaR), calculate the VaR using Monte Carlo simulation. From the results and analysis conducted on a group of SMInfra18 stocks, there are two stocks into the portfolio with an allocation of the largest given to the ISAT (PT. Indosat, Tbk) and the allocation of funds smallest given to stock TBIG (PT. Tower Bersama Infrastructure Tbk). While the losses or the estimated risk of the portfolio at 95% confidence level is IDR 18,860,237.00 of the initial capital of IDR 1,000,000,000.00 during the holding period 1 day after portfolio formation. Keywords: Stock, Portfolio, SMInfra18, CAPM, Monte Carlo

ANALISIS FAKTOR-FAKTOR YANG MEMPENGARUHI PERSENTASE PENDUDUK MISKIN DI JAWA TENGAH DENGAN METODE GEOGRAPHICALLY WEIGHTED PRINCIPAL COMPONENTS ANALYSIS (GWPCA) ADAPTIVE BANDWIDTH Mas'ad, Mas'ad; Yasin, Hasbi; Maruddani, Di Asih I
Jurnal Gaussian Vol 5, No 3 (2016): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Poverty is one of the fundamental problems that is faced by developing country such as Indonesia. One of provinces with high poverty in Java is Central Java. The factors affecting poverty in the districts/cities in Central Java are Human Development Index, pre-prosperous family, population density, Labor Force Participation Rate, and Regional Minimum Wage. Variables which is affecting poverty percentage are multivariate data that have spatial effect and are correlated to each other. Therefore, Geographically Weighted Principal Components Analysis (GWPCA) Adaptive Bandwidth is suitable to analyze what dominant factor that effects poverty percentage in the districts/cities in Central Java. GWPCA Adaptive Bandwidth is a multivariate analysis method that is used to remove the correlation in multivariate data that have spatial effects with the distance weighting measure and the extent of location influence relative to each other location conforming to the variance size of data density. The result of this research the variables affecting poverty percentage each region can be replaced by new variables called principal components which can explain 82% of the original variables. This research also found five regional groups that have different poverty-percentage-affecting characterics. Keywords : poverty, multivariate, correlation, spatial effect, GWPCA adaptive bandwidth.

VALUASI COMPOUND OPTION PUT ON PUT TIPE EROPA Sutarno, Yulia Agnis; Maruddani, Di Asih I; Sugito, Sugito
Jurnal Gaussian Vol 3, No 3 (2014): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Options are one of the form of investment which a contract that gives the right (not obligation) to the option holder to buy (call options) or sell (put options) the underlying asset by a certain date for a certain price. Option price is a reflection of the intrinsic value of the option and any additional amount over intrinsic value. One type of options that are traded is compound options. Compound option model is introduced by Robert Geske in 1979. Compound options are options on options. Compound option put on a put is put option where the underlying assets are another put option. The compound option put on put will be exercised on the first exercise date only if the value of the put option on that date is less than the first stike price. An empirical study using compound option put on a put stocks of Apple Inc which is strike price compound option US$ 560, strike price put option US$ 585, with the first exercise date on March 28, 2014 and the second exercise date on May 17, 2014. The theoritical price of compound option put on put on stocks of Apple Inc is US$ 501.4566.

PERBANDINGAN MODEL REGRESI STRATIFIED COX DAN EXTENDED COX PADA ANALISIS SURVIVAL PENDERITA KANKER PAYUDARA Samosir, Jessika Aurora; sudarno, sudarno; Maruddani, Di Asih I
Jurnal Gaussian Vol 13, No 1 (2024): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/j.gauss.13.1.59-69

Breast cancer is a tumor that develops in the breast where cells in the mammary gland divide and develop uncontrollably. Breast cancer is the most common cancer that causes death in women among other cancers. This study aims to determine the factors that affect the survival of breast cancer patients from the METABRIC database. This study was analyzed using survival analysis method. The method that is often used is the Cox proportional hazard model where the proportional hazard assumption must be met. There is variable that do not meet the assumption so that the methods used are stratified Cox and extended Cox. The stratified Cox model overcomes variables that do not meet the assumption by stratifying variables that do not meet the assumption. The extended Cox model overcomes variables that do not meet the assumption by interacting the variables with a time function. The time functions used in this study are linear time functions and logarithmic time functions. Based on the smallest AIC value, the best model is the stratified Cox regression model without interaction. Factors that affect the survival of breast cancer patients from the METABRIC database are tumor size, chemotherapy, stage 1, stage 2, and type of surgery.

PEMBENTUKAN PORTOFOLIO OPTIMAL DENGAN METODE MEDIAN VARIANCE PADA SAHAM JAKARTA ISLAMIC INDEX (JII) SEKTOR CONSUMER GOODS Faadillah, Muhamad Nabil; Maruddani, Di Asih I; Hakim, Arief Rachman
Jurnal Gaussian Vol 12, No 4 (2023): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/j.gauss.12.4.487-498

Investment is an activity to place owned assets or funds in a product hoping that there will be profits in the future. This case study was conducted by calculating the optimal portfolio using the median variance and calculating Value at Risk (VaR) using the historical simulation method. Median Variance in portfolio optimization is more suitable to be used as an investment guide because the method is not fixated on the normality distribution of the data. The data used is the Jakarta Islamic Index (JII) daily stock price data for 1 year period, which start from April 23th 2021 until April 23th 2022. The stock price used in this research is the closing price data each day during the period. The return data is used to find the weight using Median Variance method so that an optimal portfolio is formed. it is known that the Value at Risk with a confidence level of 95% and the next 1-day time period is -0,024088232 or -2,41% by investing 1% of the funds into UNVR.JK shares., by 58 % to shares of ICBP.JK, by 57% to shares of INDF.JK, by 1% to shares of JPFA.JK, and the last -17% to KLBF.JK shares is 2.41%.

Co-Authors Abdul Hoyyi Abdurakhman Abdurakhman Ari Purbowati Arief Rachman Hakim Danang Chandra Pradana, Danang Chandra Emy Siswanah Faadillah, Muhamad Nabil Hasbi Yasin Mas'ad, Mas'ad Rokhma Al Anisah Samosir, Jessika Aurora Sinambela, Nadiyah Hafidah Sudarno Sudarno Sugito - Tarno Tarno Trimono, Trimono Tutut Dewi Astuti Utami, Rianti Siswi Yuciana Wilandari Yulia Agnis Sutarno

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