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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Media Statistika Sosiohumaniora Jurnal Ilmu Dasar Statistika Proceedings of Annual International Conference Syiah Kuala University - Life Sciences & Engineering Chapter CAUCHY: Jurnal Matematika Murni dan Aplikasi TELKOMNIKA (Telecommunication Computing Electronics and Control) Bulletin of Electrical Engineering and Informatics JUTI: Jurnal Ilmiah Teknologi Informasi Journal of the Indonesian Mathematical Society Jurnal Matematika & Sains Jurnal Optimasi Sistem Industri SEMIRATA 2015 International Journal of Advances in Intelligent Informatics Indonesian Journal of Science and Technology Jurnal Teknik Industri: Jurnal Keilmuan dan Aplikasi Teknik Industri Jurnal TAM (Technology Acceptance Model) BAREKENG: Jurnal Ilmu Matematika dan Terapan International Journal of Supply Chain Management Eksakta : Berkala Ilmiah Bidang MIPA Jurnal Aplikasi Statistika & Komputasi Statistik Journal of Islamic Monetary Economics and Finance Indonesian Journal of Electrical Engineering and Computer Science JINAV: Journal of Information and Visualization Journal of Applied Data Sciences Prosiding Seminar Nasional Official Statistics Jurnal Matematika Integratif Literatur : Jurnal Bahasa dan Sastra Jurnal TAM (Technology Acceptance Model)
Dedi Rosadi
Department Of Mathematics, Universitas Gadjah Mada
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Journal : Media Statistika

 1 
PEMODELAN KURVA IMBAL HASIL DAN KOMPUTASINYA DENGAN PAKET SOFTWARE RCMDRPLUGIN.ECONOMETRICS Rosadi, Dedi
MEDIA STATISTIKA Vol 4, No 1 (2011): Media Statistika
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (238.617 KB) | DOI: 10.14710/medstat.4.1.47-55

Abstract

In this paper discussed the yield curve modeling methodology using the Nelson-Siegel model Svenson (Svensson, 1994) with special application to model the Indonesian Government Securities Yield Curve. The focus of this study is the computation of the yield curve model using the R, especially using a tool called the R-GUI RcmdrPlugin.Econometrics (Rosadi, 2011). For the empirical illustration, also given examples of applications using real data from the Indonesian capital market.   Keywords: Kurva yield, R-GUI, Nelson-Siegel-Svenson
SUSCEPTIBLE INFECTED RECOVERED (SIR) MODEL FOR ESTIMATING COVID-19 REPRODUCTION NUMBER IN EAST KALIMANTAN AND SAMARINDA Sifriyani, Sifriyani; Rosadi, Dedi
MEDIA STATISTIKA Vol 13, No 2 (2020): Media Statistika
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/medstat.13.2.170-181

Abstract

Modeling and analysis of Covid-19 data, especially on the modeling the spread and the prediction of the total number of cases for Indonesian data, has been conducted by several researchers. However, to the best of our knowledge, it has not been studied specifically for East Kalimantan Province data. The study of the data on the level of provincial and District/City level could help the government in making policies. In this study, we estimate the Covid-19 reproduction number, calculate the rate of recovery, the rate of infection, and the rate of death of East Kalimantan Province and Samarinda City. We also provide a prediction of the peak of the infection cases and forecast the total incidence of Covid-19 cases until the end of 2020. The model used in this research is the Susceptible Infected Recovered (SIR) model and the data used in the study was obtained from the East Kalimantan Public Health Office.
SELECTION OF INPUT VARIABLES OF NONLINEAR AUTOREGRESSIVE NEURAL NETWORK MODEL FOR TIME SERIES DATA FORECASTING Hermansah, Hermansah; Rosadi, Dedi; Abdurakhman, Abdurakhman; Utami, Herni
MEDIA STATISTIKA Vol 13, No 2 (2020): Media Statistika
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/medstat.13.2.116-124

Abstract

NARNN is a type of ANN model consisting of a limited number of parameters and widely used for various applications. This study aims to determine the appropriate NARNN model, for the selection of input variables of nonlinear autoregressive neural network model for time series data forecasting, using the stepwise method. Furthermore, the study determines the optimal number of neurons in the hidden layer, using a trial and error method for some architecture. The NARNN model is combined in three parts, namely the learning method, the activation function, and the ensemble operator, to get the best single model. Its application in this study was conducted on real data, such as the interest rate of Bank Indonesia. The comparison results of MASE, RMSE, and MAPE values with ARIMA and Exponential Smoothing models shows that the NARNN is the best model used to effectively improve forecasting accuracy.
PEMILIHAN PORTFOLIO ROBUST DENGAN KLROBUST PORTFOLIO SELECTION WITH CLUSTERING BASED ON BUSINESS SECTOR OF STOCKS ASTERING BERDASARKAN SEKTOR USAHA SAHAM Gubu, La; Rosadi, Dedi; Abdurakhman, Abdurakhman
MEDIA STATISTIKA Vol 14, No 1 (2021): Media Statistika
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/medstat.14.1.33-43

Abstract

In recent years there have been numerous studies on portfolio selection using cluster analysis in conjunction with Markowitz model which used mean vectors and covariance matrix that are estimated from a highly volatile data. This study presents a more robust way of portfolio selection where stocks are grouped into clusters based on business sector of stocks. A representative from each cluster is selected from each cluster using Sharpe ratio to construct a portfolio and then optimized using robust FCMD and S-estimation. Calculation Sharpe ratio showed that this method works efficiently on large number of data while also robust against outlier in comparison to k-mean clustering. Implementation of this method on stocks listed on the Indonesia Stock Exchange, which included in the LQ-45 indexed for the period of August 2017 to July 2018 showed that portfolio performance obtained using clustering base on business sector of stocks combine with robust FMCD estimation is outperformed the other possible combination of the methods.
PREDICTION OF FOREST FIRE USING NEURAL NETWORKS WITH BACKPROPAGATION LEARNING AND EXREME LEARNING MACHINE APPROACH USING METEOROLOGICAL AND WEATHER INDEX VARIABLES Rosadi, Dedi; Arisanty, Deasy; Agustina, Dina
MEDIA STATISTIKA Vol 14, No 2 (2021): Media Statistika
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/medstat.14.2.118-124

Abstract

Forest fire is one of important catastrophic events and have great impact on environment, infrastructure and human life. In this study, we discuss the method for prediction of the size of the forest fire using the hybrid approach between Fuzzy-C-Means clustering (FCM) and Neural Networks (NN) classification with backpropagation learning and extreme learning machine approach. For comparison purpose, we consider a similar hybrid approach, i.e., FCM with the classical Support Vector Machine (SVM) classification approach. In the empirical study, we apply the considered methods using several meteorological and Forest Weather Index (FWI) variables. We found that the best approach will be obtained using hybrid FCM-SVM for data training, where the best performance obtains for hybrid FCM-NN-backpropagation for data testing.
VARIANCE GAMMA PROCESS WITH MONTE CARLO SIMULATION AND CLOSED FORM APPROACH FOR EUROPEAN CALL OPTION PRICE DETERMINATION Hoyyi, Abdul; Abdurakhman, Abdurakhman; Rosadi, Dedi
MEDIA STATISTIKA Vol 14, No 2 (2021): Media Statistika
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/medstat.14.2.183-193

Abstract

The Option is widely applied in the financial sector.  The Black-Scholes-Merton model is often used in calculating option prices on a stock price movement. The model uses geometric Brownian motion which assumes that the data is normally distributed. However, in reality, stock price movements can cause sharp spikes in data, resulting in nonnormal data distribution. So we need a stock price model that is not normally distributed. One of the fastest growing stock price models today is the  process exponential model. The  process has the ability to model data that has excess kurtosis and a longer tail (heavy tail) compared to the normal distribution. One of the members of the  process is the Variance Gamma (VG) process. The VG process has three parameters which each of them, to control volatility, kurtosis and skewness. In this research, the secondary data samples of options and stocks of two companies were used, namely zoom video communications, Inc. (ZM) and Nokia Corporation (NOK).  The price of call options is determined by using closed form equations and Monte Carlo simulation. The Simulation was carried out for various  values until convergent result was obtained.
CREDIT SPREADS PADA REDUCED-FORM MODEL Di Asih I Maruddani; Dedi Rosadi; Gunardi Gunardi; Abdurakhman Abdurakhman
MEDIA STATISTIKA Vol 4, No 1 (2011): Media Statistika
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (319.946 KB) | DOI: 10.14710/medstat.4.1.57-63

Abstract

There are two primary types of models in the literature that attempt to describe default processes for debt obligations and other defaultable financial instruments, usually referred to as structural and reduced-form (or intensity) models. Structural models use the evolution of firms’ structural variables, such as asset and debt values, to determine the time of default. Reduced form models do not consider the relation between default and firm value in an explicit manner. Reduced form models assume that the modeler has the same information set as the market - incomplete knowledge of the firm’s condition. that leads to an inaccessible default time. The key distinction between structural and reduced form models is not whether the default time is predictable or inaccessible, but whether the information set is observed by the market or not. Consequently, for pricing and hedging, reduced form models are the preferred methodology. Credit spreads are used to measure credit premium, which compensates risk-averse investors for assuming credit risk. Therefore, the credit spreads should remain positive. The higher credit risk assumed by the investors, the higher credit premium got be payed by them. In this paper, we have to to determine the credit spreads of reduced-form model.   Keywords: Reduced-Form Model, Hazard Rate, Credit Spreads  
FORECASTING COVID-19 IN INDONESIA WITH VARIOUS TIME SERIES MODELS Gumgum Darmawan; Dedi Rosadi; Budi Nurani Ruchjana; Resa Septiani Pontoh; Asrirawan Asrirawan; Wirawan Setialaksana
MEDIA STATISTIKA Vol 15, No 1 (2022): Media Statistika
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/medstat.15.1.83-93

Abstract

In this study, Covid-19 modeling in Indonesia is carried out using a time series model. The time series model used is the time series model for discrete data. These models consist of Feedforward Neural Network (FFNN), Error, Trend, and Seasonal (ETS), Singular Spectrum Analysis (SSA), Fuzzy Time Series (FTS), Generalized Autoregression Moving Average (GARMA), and Bayesian Time Series. Based on the results of forecast accuracy calculation using MAPE (Mean Absolute Percentage Error) as model evaluation for confirmed data, the most accurate case models is the bayesian model of 0.04%, while all recovered cases yield MAPE 0.05%, except for FTS = 0.06%. For data for death cases SSA and Bayesian Models, the best with MAPE is 0.07%.
MEASUREMENT OF SUPPORT VECTOR REGRESSION PERFORMANCE WITH CLUSTER ANALYSIS FOR STOCK PRICE MODELING Izza Dinikal Arsy; Dedi Rosadi
MEDIA STATISTIKA Vol 15, No 2 (2022): Media Statistika
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/medstat.15.2.163-174

Abstract

Risk-averse investors will seek out stock investments with the minimum risk. One step that can be taken is to develop a model of stock prices and predict their fluctuations in the coming months. Significant studies on the modeling of stock movements have used the ARCH/GARCH method, but this method requires some assumptions. This paper will discuss the performance of stock modeling using Support Vector Regression. The performance is measured using the root mean square error value in two stock clusters based on its volatility value, e.g., stocks with large volatility and stocks with small volatility. This case study makes use of daily closing price data from 10 LQ-45 index shares from October 12, 2018 to October 11, 2019. In conclusion, SVR's performance on stocks with high volatility produces RMSE, which is considerably higher than SVR's performance on stocks with low volatility.
Co-Authors Abda Abda Abdul Hoyyi Abdurakhman Abdurakhman Abdurakhman Abdurakhman Abdurakhman Abdurakhman Adhitya Ronnie Effendie, Adhitya Ronnie Adi Marhadi Asrirawan Asuri, Afriza Baehaqi Budi Nurani Ruchjana Danardono Danardono Danardono, Danardono Dara Puspita Anggraeni Deasy Arisanty Dede Maryana Devni Prima Sari Di Asih I Maruddani Edi Faizal Epha Diana Supandi Ezra Putranda Setiawan Ezra Putranda Setiawan Faihatuz Zuhairoh Fajri Farid Firmansyah, Hilmi Gubu, La Gumgum Darmawan Gumgum Darmawan Hendra Perdana Hermansah Hermansah Hermansah Hermansah Hermansah Hermansah Hermansah, Hermansah Herni Utami Herni Utami Iman Sanjaya Indradewa, Rhian Iskandar, Edi Izza Dinikal Arsy Jana, Padrul Khabib Mustofa La Gubu Malim Muhammad Media Rosha Muhammad Muhajir, Muhammad Pepi Novianti Resa Septiani Pontoh Retno Subekti Rizal, Ahmad Ashril Ruchjana, Budi N Rupilu, Rina Apriany Helen Wite Setialaksana, Wirawan - Sifriyani, Sifriyani Solly Aryza Sri Redjeki Ulfasari Rafflesia