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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

Unknown Affiliation

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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PENGARUH DATA EKSTRIM ASET PERUSAHAAN PADA VALUASI OBLIGASI I Maruddani, Di Asih
Prosiding Seminar Nasional Venue Artikulasi-Riset, Inovasi, Resonansi-Teori, dan Aplikasi Statistika (VARIANSI) Vol 1 (2018)
Publisher : Program Studi Statistika, FMIPA, Universitas Negeri Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (520.966 KB)

Asumsi dasar yang sering digunakan pada valuasi obligasi merupakan penggunaan asumsi pada model Black-Scholes-Merton. Terdapat dua asumsi yang kurang tepat digunakan dalam investasi praktis obligasi, yaitu data aset perusahaan tidak mengikuti distribusi Normal, dalam hal ini memiliki data ekstrem yang diperlihatkan dengan keberadaan jump. Selain itu pemberian kupon secara periodik merupakan hal yang wajar dalam kontrak obligasi. Paper ini akan membahas secara matematis valuasi obligasi dalam hal ini memberikan nilai ekspektasi modal perusahaan dan kemungkinan kebangkrutan perusahaan yang diakibatkan perusahaan tidak mampu membayar kembali hutang obligasinya pada saat jatuh tempo. Untuk menagkap adanya jump pada data aset perusahaan, geometric Brownian motion dengan jump diffusion merupakan model yang tepat. Sedangkan pembentukan serial pemberian kupon dapat dilakukan dengan pendekatan compound option. Penerapan kasus ini adalah dengan melakukan analisis pada Obligasi Berkelanjutan II Bank CIMB Niaga Tahap III Tahun 2017 Seri C. Hasil yang diperoleh memberikan informasi yang lebih lengkap kepada investor obligasi pada saat pembayaran kupon dan saat jatuh tempo.Â Kata Kunci: obligasi, coupon, data ekstrem, compound poisson, jump diffusion process

ESTIMASI PARAMETER MODEL REGRESI NON STASIONER DENGAN VARIABEL DEPENDEN LAG : STUDI KASUS PADA PERKEMBANGAN EKSPOR INDONESIA KE JEPANG TAHUN 1980 - 2000 I Maruddani, Di Asih
MATEMATIKA Vol 7, No 1 (2004): JURNAL MATEMATIKA
Publisher : MATEMATIKA

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The clasiccal regression model was devised to handle relationship between stationary variables. But, many economic variables that frequently faced by econometricians when dealing with time series data, are nonstationary variables. This clearly places severe restrictions on their analysis by standard regression method. In this paper, we study regression models with a lagged dependent variable when both the dependent and independent variables are nonstationary, and the regression model is not cointegrated. In particular, we discuss the limiting properties of least squares estimates of the parameters in such regression models. We show that the estimate of the lagged dependent variable tends to unity and the estimates of the independent variables tend to zero. The results might also allow us to investigate the growth of export from Indonesian to Japan.

ANALISIS CLUSTER DENGAN ALGORITMA K-MEANS DAN FUZZY C-MEANS CLUSTERING UNTUK PENGELOMPOKAN DATA OBLIGASI KORPORASI Desy Rahmawati Ningrat; Di Asih I Maruddani; Triastuti Wuryandari
Jurnal Gaussian Vol 5, No 4 (2016): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Cluster analysis is a method of grouping data (object) that are based on information that found in the data which describes the object and relation within. Cluster analysis aims to make the joined objects in the cluster are identical (or related) with one another and different (not related) to objects in another cluster. In this study used two method of grouping; Fuzzy C-Means and K-Means Clustering. The data used in this research had been using 357 corporate bonds data on December 1st, 2015. The variables used in this study consist of coupon rate, time to maturity, yield and rating of each corporate. The determination of the number of optimum clusters performed by Xie Beni index of validity calculation at FCM method. Having obtained the optimum number of clusters, evaluation step was conducted by comparing FCM method to K-Means method with noticing the average of standard deviation in the clusters and the average of standard deviation inter-clusters (Sw/Sb) from each method. Method with the smallest Sw/Sb ratio value would get chosen as the best method. Based on the validity index Xie Beni, the most optimum number of cluster is 10 because it has the smallest Sw/Sb ratio value compared to FCM, the value is 0,6651. Afterwards, the result of K-Means clustering is analyzed to determined the interpretation and characteristics of each formed clusters.Keyword: Cluster Analysis, coupon rate, time to maturity, yield, rating, Fuzzy C-Means, K-Means, Xie Beni Index, Sw/Sb ratio.

STRUCTURAL VECTOR AUTOREGRESSIVE UNTUK ANALISIS DAMPAK SHOCK NILAI TUKAR RUPIAH TERHADAP DOLAR AMERIKA SERIKAT PADA INDEKS HARGA SAHAM GABUNGAN Annisa Rahmawati; Di Asih I Maruddani; Abdul Hoyyi
Jurnal Gaussian Vol 6, No 3 (2017): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Instability and depreciation of the rupiah be a motivating factor for investors to pull out a portfolio in Indonesia. The weakening of rupiah led to a decline in investor demand for stocks. Measurement of stock price fluctuations or portfolio using the Composite Stock Price Index (CSPI). The exchange rate and CSPI is a sensitive macroeconomic variables affected by shock and it takes restriction of macroeconomic structural model. Based on this, Structural Vector Autoregressive (SVAR) model is used. The purpose of this thesis is to analyze the impact of the exchange rate shock on CSPI through the description of Structural Impulse Response Function and Structural Variance Decomposition modeling based on a restriction on SVAR. SVAR also called the theoretical VAR used to respond to criticism on the VAR model where necessary the introduction of restrictions on economic models. By using daily data exchange rate of the rupiah against the US dollar and CSPI from January 2013 to December 2016 acquired the VAR model is stable and meets the white noise assumption as the basis for modeling residual SVAR and has a short-term restriction. The response of CSPI from the impact of the shock rupiah exchange rate is likely to experience an increase, while the response to the shock CSPI itself is fluctuating but tends to decrease. Patterns proportion shock effect on the exchange rate is increasingly rising stock index in the period of time, whereas the effect of the shock CSPI itself getting down on each period of time. Keywords : exchange rate, CSPI, SVAR, Structural Impulse Response Function, Structural Variance Decomposition

KLASIFIKASI PERUBAHAN HARGA OBLIGASI KORPORASI DI INDONESIA MENGGUNAKAN METODE NAIVE BAYES CLASSIFICATION Khotimatus Sholihah; Di Asih I Maruddani; Abdul Hoyyi
Jurnal Gaussian Vol 5, No 2 (2016): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Bond is a medium-long term debt securities which can be sold and contains a pledge from the issuer to pay interest for a certain period and repayment of the principal debt at a specified time to the bonds buyer. Bonds price changes any time, it could be beneficial or give disadvantage to investors. Investors should know the best conditions to buy bonds on a discount, or sell them at a premium price. By classify the changing of bonds price, it could help investors to gain optimum return. One method is Naive Bayes classification. In theory, It has the minimum error rate in comparison to all other classifiers. Bayes is a simple probabilistic-based prediction technique which based on the application of Bayes theorem with strong independence assumptions. Before classifying, preprocessing data is required as a stage feature selection. In this case, the Mann Whitney test can be done to choose the independent features of each class. Validation technique in use is k-fold cross validation. Based on analysis, we gained average accuracy at 78,52% and 21,8% error. With high accuracy and quite low error, it means that the Naïve Bayes method works quite well on classifying the corporate bonds price changes in Indonesia. Keywords: bonds, classification, k-fold cross validation, Naive Bayes

PERHITUNGAN VALUE AT RISK PADA PORTOFOLIO SAHAM MENGGUNAKAN COPULA (Studi Kasus : Saham- Saham Perusahaan di Indonesia Periode 13 Oktober 2011 - 12 Oktober 2016) Oktafiani Widya Ningrum; Tarno Tarno; Di Asih I Maruddani
Jurnal Gaussian Vol 6, No 2 (2017): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Investment is one of the way that is widely performed by people to achieve profitability in the future.Stock data is a data that is obtained from the observation that stock prices can be categorized into time series data, which usually have a tendency to fluctuate rapidly by the time so the variance of the residual will always change all the time or not constant, or often called heteroscedasticity case. Forecasting and data analysis is intended to minimize the risk and uncertainty factors. The risks can not be avoided but can be managed and estimated using Value at Risk (VaR) measurement tool. Copula theory is one of the tool that can be used to fit the joint distribution because it does not require the assumption of normality of the data so it is flexible enough for a variety of data, especially for financial data. This research is conducted using the method of Copula-GARCH to fit the three stocks of companies return data in Indonesia which have high volatility, those are PT Vale Indonesia Tbk (INCO), PT Bank Central Asia Tbk (BCA), and PT Indocement Tunggal Tbk (INTP) in period of October 13, 2011 to October 12, 2016 into ARIMA-GARCH model. The analysis is followed by copula on two stocks that have the highest ARIMA-GARCH residual correlation, those are BCA and INTP.Copula Gumbel is selected as the best copula with the amount of is 1,337. The risk derived from the calculation of Value at Risk (VaR) at the 99% confidence level is 3,922%, at the 95% confidence level is 2,397%, and at the 90% confidence level is 1,745%.Keywords : Value at Risk, Copula, GARCH

PENGUKURAN PROBABILITAS KEBANGKRUTAN DAN VALUASI OBLIGASI KORPORASI DENGAN METODE CREDITRISK+ Yudia Yustine; Abdul Hoyyi; Di Asih I Maruddani
Jurnal Gaussian Vol 1, No 1 (2012): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

In capital market investment particularly the bonds, an investor must consider the credit risk and valuation of bonds. Credit risk refers to the risk due to unexpected changes in the credit quality of a counterparty or issuer. Valuation is amount that investor will receive on future. CreditRisk+ is from Reduced-Form Model which is used to calculate the probability of default and valuation of bonds. This method assumes that default occurs without warning and is therefore unpredictable. Default arrival is described by a Poisson process. Default intensity can expected by rate of corporate. An empirical example use a data set of bond from PT Berlian Laju Tanker, Tbk between 2007 and 2012. Probability of default from Berlian Laju Tanker III Bond is 0,6321206 and its valuation is Rp 153.481.545.500,00.

PENENTUAN VALUASI PORTOFOLIO OBLIGASI DENGAN CREDIT METRICS DAN MONTE CARLO SIMULATION Arief Seno Nugroho; Di Asih I Maruddani; Sugito Sugito
Jurnal Gaussian Vol 2, No 3 (2013): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

The capital market is one way to get funding for the company and as a medium to strengthen corporate finance position. One of the instruments that are traded than stocks are bonds. The advantage of this instrument because it is easy and rapid acquisition of funds to beused for the operations of the corporate and the period of payment is longer. Bond investment must be noticed valuations and credit risk, with calculating the valuation can be estimate bonds credit risk. Credit Metrics is a reduced form model to estimate the risk of displacement of ratings. The risk not only occur when corporate rating be default but also if the rating upgrade or downgrade. For the determination of the portfolio valuation can be used Monte Carlo simulation using generate scenarios corporate ratings. Empirical study can be used for three bonds there are Obligasi II Bank Danamon Tahun 2010 Seri B, Obligasi II Telkom Tahun 2010 Seri A, and Obligasi Indofood Sukses Makmur V Tahun 2009. Each has an average valuation of 1.013,039 billion, 1.179,203 billion and 2.259,284 billion. The valuation of the portfolio amounted to 4.451,52 billion and a standard deviation 70,33 billion

ANALISIS KETAHANAN HIDUP PENDERITA DENGUE HEMORRHAGIC FEVER (DEMAM BERDARAH) DENGAN REGRESI COX KEGAGALAN PROPORSIONAL SENSOR TIPE III Studi Kasus di Rumah Sakit Umum Daerah (RSUD) Temanggung Irfan Afifi; Di Asih I Maruddani; Abdul Hoyyi
Jurnal Gaussian Vol 6, No 3 (2017): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Dengue Fever is a disease caused by the dengue virus, transmitted from person to person through the bite of Aedes Aegypti and Aedes Albopictus mosquitoes. Dengue Fever mainly found in the tropical countries, such as Indonesia. According to World Health Organization (WHO) data, Indonesia reported as the 2nd country with the largest dengue cases among 30 endemic countries between 2004 until 2010. Therefore, it is important to identify the factors influencing the recovery speed of dengue patients. This study utilize statitistical approach through regression analysis. One of the analysis methode choosen is survival analysis. This analysis is utilized to figure out the time series data analysis, of origin undefined time until the occurrence of certain events. In Survival Analysis, one of the regression method which is commonly used is Cox regression. This study uses statistical methods approach through Cox regression proportional hazard to take into consideration the time of failure as the dependent variable. as well as the response variable function tends to a constant failure. object of research in this study are patients with dengue fever and the time the patient entered in a separate viewing the selected sensor type III This study used medical records of dengue fever patients of regional public hospital in Temanggung City, Central Java, from period of January to November 2016. Results obtained shows that the factors affecting the recovery speed of patients is Hematocrit state of the patient. Patients with normal Hematocrit state have faster recovery that patients with upnormal circumtances. Keywords: Dengue, Survival Analysis, Regression Cox Proportional Hazard

RISIKO KREDIT PORTOFOLIO OBLIGASI DENGAN CREDIT METRICS DAN OPTIMALISASI PORTOFOLIO DENGAN METODE MEAN VARIANCE EFFICIENT PORTFOLIO (MVEP) Nurul Fauziah; Abdul Hoyyi; Di Asih I Maruddani
Jurnal Gaussian Vol 1, No 1 (2012): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Investing is a important thing in a capital market. Bond investment must be noticed the risk especially credit risk. From the information of credit risk, investor can choose the right investment. Credit Metrics is a reduced form model to estimate the risk. Credit Metrics is centered by the corporate rating. The risk not only occur when corporate rating be default but also if the rating upgrade or downgrade. For a bond portfolio, can calculate the optimal portfolio by Mean Variance Efficient Portfolio method. Empirical study can be used for two bonds, first bond is Obligasi Adira Dinamika Multi Finance V Tahun 2011 Seri A and second one is Obligasi BFI Finance Indonesia III Tahun 2011 Seri A. First bond has 127.01640 (Billion) of credit risk and the second one bonds has 18.33472 (Billion). For a portfolio of that two bonds, they have 179.82460 (Billion). For the optimal portfolio, first bond has propotion 66.39% and 33.61% for the second bond.

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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