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All Journal Media Statistika MATEMATIKA Jurnal Gaussian Seminar Nasional Variansi (Venue Artikulasi-Riset, Inovasi, Resonansi-Teori, dan Aplikasi Statistika) (JRAMB) Jurnal Riset Akuntansi Mercu Buana International Journal of Data Science, Engineering, and Analytics (IJDASEA) Prosiding Seminar Nasional Unimus

Di Asih I Maruddani

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Author-ID : 284298

Humanities Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Health Professions Mathematics Nursing Public Health Other

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PEMODELAN FIXED EFFECT GEOGRAPHICALLY WEIGHTED PANEL REGRESSION UNTUK INDEKS PEMBANGUNAN MANUSIA DI JAWA TENGAH Siti Maulina Meutuah; Hasbi Yasin; Di Asih I Maruddani
Jurnal Gaussian Vol 6, No 2 (2017): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Human development index is an indicator for assessing the quality of human resources and measure the results of human development. The achievements of the human development index is not enough if conducting observations in each cities in just one particular time, but the observations need to be made in some period of time. The distribution in each cities is also a concern, because the conditions are so diverse that led to their spatial effects. Therefore, it is necessary to study these variables in some time periods that affect human development index taking into account the spatial effects. Statistical methods used to overcome their spatial effects, especially in the problem of spatial heterogeneity in the data type of panel is Geographically Weighted Panel Regression (GWPR). This study focused on the establishment of GWPR model with fixed effects using fixed exponential kernel on the human development index data cities in Central Java in 2010-2015. The results of this study indicate that the fixed effect model GWPR differ significantly on panel data regression model, and the model generated for each location will be different from one another. In addition, cities in Central Java has five groups based on variables that are significant. In the fixed effect model GWPR generates R2 value of 92.27%.Keywords: Human Development Index, Panel Data, Spatial Effects, Fixed Effect, Fixed Exponential Kernel, Geographically Weighted Panel Regression, R2.

PENGUKURAN PROBABILITAS KEBANGKRUTAN OBLIGASI KORPORASI DENGAN SUKU BUNGA VASICEK MODEL MERTON (Studi Kasus Obligasi PT Bank Lampung, Tbk) Kumo Ratih; Di Asih I Maruddani; Abdul Hoyyi
Jurnal Gaussian Vol 1, No 1 (2012): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Bond is one of financial instrument that have lower investment risk than stock. One of investment risk is credit risk. Its refers to the risk due to unexpected changes in the credit quality of a counterparty or issuer on maturity date. There are two ways in the modelling of credit risk, structural model and reduced models. The structural model introduced by Black-Scholes (1973) and Merton (1974). On the Merton model assume that default occurs when the firm can not pay the coupon or face value at the maturity date. The interest rate on this model asssumed following Vasicek rate. An empirical study using corporate bond of PT Bank Lampung, Tbk with 300 billion face value. Value of Probability of Default 0,0000007910811% provethat PT Bank Lampung still can full their obigation at November 2012.

PENERAPAN MODEL INDEKS TUNGGAL UNTUK OPTIMALISASI PORTOFOLIO DAN PENGUKURAN VALUE AT RISK DENGAN VARIANCE COVARIANCE (Studi Kasus: Saham yang Stabil dalam LQ 45 Selama Periode Februari 2011 – Juli 2016) Hanifa Eka Oktafiani; Di Asih I Maruddani; Suparti Suparti
Jurnal Gaussian Vol 6, No 1 (2017): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

One of popular investments among investors is investing in a form of stock in go public companies. Investing stocks must not be separated from a wide variety of risks. One way to minimize risk is by taking a portfolio of several stocks. This research uses single index model to form portfolio of several stocks because it has simple computation than other method. This model based on the observation that price of securities have linier fluctuation with market indeks. Estimate of Value at Risk (VaR) can be calculated using variance covariance method which requires that return of a stock and return portfolio of several stocks have a normal distribution. This research aplicated to stable several stocks, in the meaning that always recorded in LQ 45 during February 2011 until July 2016. Based on 21 stable stocks in LQ 45, there are six stocks included in the optimal portfolio. That is stock of GGRM (Gudang Garam Ltd.), BBCA (Bank Central Asia Ltd.), JSMR (Jasa Marga Persero Ltd.), LPKR (Lippo Karawaci Ltd.), BBRI (Bank Rakyat Indonesia Persero Ltd.), and INDF (Indofood Sukses Makmur Ltd.), which estimated of VaR in a month after investing on optimal portfolio at 95% confidence level is Rp 7.846.572,00 from initial capital of Rp 100.000.000,00. Keywords: Portfolio, Stock, Single Index Model, Variance Covariance, LQ 45

ANALISIS DATA RUNTUN WAKTU MENGGUNAKAN METODE WAVELET THRESHOLDING DENGAN MAXIMAL OVERLAP DISCRETE TRANSFORM Dyah Ayu Kusumaningrum; Suparti Suparti; Di Asih I Maruddani
Jurnal Gaussian Vol 6, No 1 (2017): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Wavelet is a mathematical tool for analyzing time series data. Wavelet has certain properties one of which is localized in the time domain and frequency and form an orthogonal basis in the space L2(R). There are two types of wavelet estimators are linear and nonlinear wavelet estimators. Linear wavelet estimators can be analyzed using the approach of Multiresolution Analysis (MRA), while nonlinear wavelet estimator called Wavelet Thresholding. Wavelet thresholding are emphasizing the reconstruction of wavelet using a number of the largest coefficient or can be said that only coefficient greater than a value taken, while other coefficients are ignored. There’re several factors that affect the smooth running of the estimation are the type of wavelet function, types of functions of thresholding, thresholding parameters, and the level of resolution. Therefore, in this thesis will have optimal threshold value in analyzing the data. Wavelet Thresholding method provides value of Mean Square Error (MSE) that smaller compare to wavelet method with the approach Multiresolution Analysis (MRA). In this case study Wavelet Thresholding are considered better in the analysis of time series data. Keywords: Multiresolution Analysis, Wavelet Thresholding Estimator.

VALUASI COMPOUND OPTION PUT ON CALL TIPE EROPA PADA DATA SAHAM FACEBOOK Muhammad Sunu Widianugraha; Di Asih I Maruddani; Diah Safitri
Jurnal Gaussian Vol 4, No 2 (2015): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Option is a contract that gives the right to individuals to buy (call options) or sell (put options) the underlying asset by a certain price for a certain date. One type of options that are traded is compound options. Compound option model is introduced by Robert Geske in 1979. Compound option is option on option. Compound option put on a call is put option where the underlying asset are call option. An empirical study using compound option put on a call stocks of Facebook. It has strike price compound option US$ 77.5 and strike price call option US$ 80, with the first exercise date on September 26, 2014 and the second exercise date on October 31, 2014. The theoritical price of compound option put on call on stocks of Facebook is US$ 75.65048. Keywords: Compound option, put on a call, option stocks of Facebook, Black-Scholes model, theoritical price.

ANALISIS FAKTOR-FAKTOR YANG MEMPENGARUHI DIVIDEND PAYOUT RATIO (DPR) MENGGUNAKAN ANALISIS REGRESI LINIER DENGAN BOOTSTRAP (Studi Kasus: PT. Unilever Indonesia, Tbk Tahun 1999-2015) Lia Safitri; Di Asih I Maruddani; Rukun Santoso
Jurnal Gaussian Vol 6, No 3 (2017): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

The amount of dividend paid by the company to shareholders or dividend payout ratio is the main factor that investors pay attention to invest their capital into the company. Investors want a relative dividend, even increasing over time. Factors influencing the level of dividend payout ratio are Return on Equity (ROE), stock price, liquidity ratio, and leverage level. Based on this, multiple linear regression analysis with bootstrap is used. The purpose of this study is to analyze the factors that significantly affect the dividend payout ratio based on the best model used to predict the value of dividend payout ratio for the next period. The bootstrap method is used to overcome the occurrence of multicollinearity among independent variables due to the small sample size. Based on the simulation done with software R using PT data. Unilever Indonesia, Tbk from 1999-2015 obtained best model is bootstrap residual with 2 significant independent variable are ROE and level of leverage. Based on the best model, the predicted value of dividend payout ratio of 2016 is 41.60196 with percentage error of 7.0812%. Keywords : Regression analysis, Bootstrap, Dividend Payout Ratio, ROE, leverage

PEMODELAN HARGA SAHAM DENGAN GEOMETRIC BROWNIAN MOTION DAN VALUE AT RISK PT CIPUTRA DEVELOPMENT Tbk Trimono Trimono; Di Asih I Maruddani; Dwi Ispriyanti
Jurnal Gaussian Vol 6, No 2 (2017): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Financial sector investment is an activity that attracts a lot of public interest. One of them is investing funds in purchasing company’s shares. Profit received from stock investment activity can be seen from the value of stock returns. While, if the previous stock returns Normal distribution, the future stock price can be predicted by Geometric Brownian Motion Method. Based on the stock price prediction, can also be measured an estimated value of the investment risk. The result of data processing shows that the stock price prediction of PT. Ciputra Development Tbk period December 1, 2016 untuk January 31, 2017, has very good accuracy, based on the value of MAPE 1.98191%. Further, Value at Risk Method of Monte Carlo Simulation with α = 5% significance level was used to measure the share investment risk of PT.Ciputra Development Tbk. Thus, this method is only useful if it can be used to predict accurately. Therefore, backtesting is needed. Based on the processing obtained data, backtesting generates the value of violation ratio at 0, it means that at significance level α = 5%, Value at Risk Method of Monte Carlo Simulation can be used at all levels of probability violation.. Keywords : Geometric Brownian Motion, Risk, Value at Risk, Backtesting

PENGUKURAN RISIKO KREDIT OBLIGASI KORPORASI DENGAN CREDIT VALUE AT RISK (CVAR) DAN OPTIMALISASI PORTOFOLIO MENGGUNAKAN METODE MEAN VARIANCE EFFICIENT PORTFOLIO (MVEP) Agus Somantri; Di Asih I Maruddani; Abdul Hoyyi
Jurnal Gaussian Vol 2, No 3 (2013): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Getting benefits of many kinds of coupon is not the only advantage of bond investment, but also it gives potential risks such as credit risk. Credit risk originates from the fact that counterparties may be unable to fulfill their contractual obligations. Credit Value at Risk (CVaR) is introduced as a method to calculate bond credit risk if default occurs. CVaR is defined as the most significant credit loss which occurs unexpectedly at the selected level of confidence, measured as the deviation of Expected Credit Loss (ECL). To construct optimal bond portfolio requires Mean variance Efficient Portfolio (MVEP) method. MVEP is defined as the portfolio with minimum variance among all possible portfolios that can be formed. This study case has been constructed through two bonds, bond VI of Jabar Banten Bank (BJB) year 2009 serial B and bond of BTPN Bank I year 2009 serial B. Based on the R programming output, the obtained results for bonds with a rating idAA BJB, has a positive CVaR value of Rp 22.728.338,00. While bonds with a rating idAA BTPN and portfolio for both bonds, each of which has a negative CVaR value amounted Rp 28.759.098,00 and Rp 32.187.425,00. CVaR is positive (+) expressed as the loss addition of ECL while is negative () expressed as a decrease in loss of ECL. For optimal bond portfolio, gained weight for each bond is equal to 16,85202% for BJB and 83,14798% for BTPN bonds.

Prediksi harga saham PT. Astra agro lestari TBK dengan jump diffusion model Di Asih I Maruddani; Trimono Trimono
(JRAMB) Jurnal Riset Akuntansi Mercu Buana Vol 3, No 1: Mei 2017
Publisher : Universitas Mercu Buana Yogyakarta

Saham merupakan salah satu emiten yang paling banyak diperjualbelikan di pasar modal. Harga saham dan perubahannya merupakan dua indikator yang sering dijadikan bahan pertimbangan oleh para calon investor sebelum memutuskan untuk membeli saham suatu perusahaan. Harga saham hampir selalu mengalami perubahan, dan sulit diperkirakan bagaimana keadaannya pada periode yang akan datang. Terdapat berbagai metode yang dapat digunakan untuk memperikirakan harga saham pada periode yang akan datang. Diantaranya adalah pemodelan dengan Geometric Brownian Motion (GBM) dan pemodelan dengan GeometricBrownian Motion (GBM) dengan Jump. Metode GBM dapat memperediksi harga saham dengan baik apabila data return saham periode sebelumnya berdistribusi normal. Sedangkan jika pada data return saham periode sebelumnya memenuhi asumsi normalitas dan ditemukan adanya lompatan, maka digunakan metode Jump Diffusion. Prediksi harga saham AALI untuk periode 03/01/2017 sampai dengan 12/05/2017 dengan GBM menghasilkan akurasi peramalan yang baik, dengan nilai MAPE sebesar 11,26%. Prediksi harga saham AALI untuk periode 03/01/2017 sampai dengan 12/05/2017 dengan metode Jump Diffuison menghasilkan akurasi peramalan yang sangat baik, dengan nilai MAPE sebesar 2,60%. Berdasarkan nilai MAPE, model Jump Diffusion memberikan hasil yang lebih baik daripada model GBM.

Geometric Brownian Motion and Value at Risk For Analysis Stock Price Of Bumi Serpong Damai Ltd Trimono Trimono; Di Asih I Maruddani; Prisma Hardi Aji Riyantoko; I Gede Susrama Mas Diyasa
Internasional Journal of Data Science, Engineering, and Anaylitics Vol. 1 No. 1 (2021): International Journal of Data Science, Engineering, and Analytics Vol 1, No 1,
Publisher : International Journal of Data Science, Engineering, and Analytics

Investment is one of the activities that last actually attractive to the people of Indonesia. One of the most widely traded financial assets in the capital market is stocks. Stock prices frequently experience challenges to predict changes, so they can increase or decrease at any time. One method that can be applied to predict stock prices is GBM. Then, the risk can be measured using the VaR risk measure. The GBM model is determined to be accurate in predicting the stock price of BSDE.JK, with a MAPE value of 5.17%. By using VaR-HS and VaR CFE, the prediction of risk of loss at the 95% confidence level for the period 06/07/21 is -0.0597 and -0.0623

Co-Authors Abdul Hoyyi Abdurakhman Abdurakhman Agus Somantri ANNISA RAHMAWATI Arief Seno Nugroho Azzarah, Dian Fatimah Budi Warsito Dedi Rosadi Desy Rahmawati Ningrat Diah Safitri Dwi Ispriyanti Dyah Ayu Kusumaningrum Endang Purbowati Gunardi Gunardi Hanifa Eka Oktafiani Hasbi Yasin I Gede Susrama Mas Diyasa Irfan Afifi Khotimatus Sholihah Kumo Ratih Lia Safitri Masithoh Yessi Rochayani Moch. Abdul Mukid Muhammad Sunu Widianugraha Nurul Fauziah Oktafiani Widya Ningrum Prisma Hardi Aji Riyantoko Reihanah, Khalifah Nadya Rukun Santoso Siti Maulina Meutuah Sri Sumiyati Sugito Sugito Suparti Suparti Tarno Tarno Tatik Widiharih Triastuti Wuryandari Trimono Trimono Trimono, Trimono Yudia Yustine

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