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E-Jurnal Matematika
Published by Universitas Udayana
ISSN : 23031751     EISSN : -     DOI : -
Core Subject : Education,
Mathematics
E-Jurnal Matematika merupakan salah satu jurnal elektronik yang ada di Universitas Udayana, sebagai media komunikasi antar peminat di bidang ilmu matematika dan terapannya, seperti statistika, matematika finansial, pengajaran matematika dan terapan matematika dibidang ilmu lainnya. Jurnal ini lahir sebagai salah satu bentuk nyata peran serta jurusan Matematika FMIPA UNUD guna mendukung percepatan tercapainya target mutu UNUD, selain itu jurnal ini terbit didorong oleh surat edaran Dirjen DIKTI tentang syarat publikasi karya ilmiah bagi program Sarjana di Jurnal Ilmiah. E-jurnal Matematika juga menerima hasil-hasil penelitian yang tidak secara langsung berkaitan dengan tugas akhir mahasiswa meliputi penelitian atau artikel yang merupakan kajian keilmuan.
Arjuna Subject : -
Articles 8 Documents
 1 
Search results for , issue "Vol 4 No 2 (2015)" : 8 Documents clear
MENENTUKAN HARGA KONTRAK BERJANGKA NILAI TUKAR RUPIAH TERHADAP DOLLAR AS MENGGUNAKAN DISTRIBUSI LOGNORMAL GEDE SUMENDRA; KOMANG DHARMAWAN; I NYOMAN WIDANA
E-Jurnal Matematika Vol 4 No 2 (2015)
Publisher : Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/MTK.2015.v04.i02.p087

Abstract

The purpose of this study is to determine the fair price of a futures contract for the IDR (Rupiah) against the USD using lognormal distribution simulation. This result is compared with interest rate parity theorem. The first step of this study is to determine the values of the parameters which are optimized using Maximum Likelihood Estimation (MLE). The parameters obtained in the form of the mean () and variance (). Further, parameters obtained are simulated using lognormal distribution to determine the exchange rate simulation (). Then price of future contract is also calculated using interest rate parity theorem. The price of the futures contracts () is determined by lognormal distribution simulated and price of interest rate futures contracts using parity theorem. The results of this study show that future contract price over the fair use lognormal distribution of 12.215 compared to the interest rate parity theorem which 12.400, with the initial contract price () of 12.185.
PENDUGAAN DATA HILANG DENGAN METODE YATES DAN ALGORITMA EM PADA RANCANGAN LATTICE SEIMBANG MADE SUSILAWATI; KARTIKA SARI
E-Jurnal Matematika Vol 4 No 2 (2015)
Publisher : Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/MTK.2015.v04.i02.p092

Abstract

Missing data often occur in agriculture and animal husbandry experiment. The missing data in experimental design makes the information that we get less complete. In this research, the missing data was estimated with Yates method and Expectation Maximization (EM) algorithm. The basic concept of the Yates method is to minimize sum square error (JKG), meanwhile the basic concept of the EM algorithm is to maximize the likelihood function. This research applied Balanced Lattice Design with 9 treatments, 4 replications and 3 group of each repetition. Missing data estimation results showed that the Yates method was better used for two of missing data in the position on a treatment, a column and random, meanwhile the EM algorithm was better used to estimate one of missing data and two of missing data in the position of a group and a replication. The comparison of the result JKG of ANOVA showed that JKG of incomplete data larger than JKG of incomplete data that has been added with estimator of data. This suggest  thatwe need to estimate the missing data.
PENERAPAN REGRESI PROBIT BIVARIAT UNTUK MENDUGA FAKTOR-FAKTOR YANG MEMENGARUHI KELULUSAN MAHASISWA (Studi Kasus: Mahasiswa Fakultas MIPA Unversitas Udayana) NI GUSTI KETUT TRISNA PRADNYANTARI; I KOMANG GDE SUKARSA; NI LUH PUTU SUCIPTAWATI
E-Jurnal Matematika Vol 4 No 2 (2015)
Publisher : Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/MTK.2015.v04.i02.p088

Abstract

The aim of this research to estimate the factors that affect students graduation using bivariate probit regression. Bivariate probit regression is a statistical method that involves two response variables which are qualitative and the independent variables are qualitative, quantitative, or a combination of both. In bivariate probit regression model, the result obtained is the probability of the response variable. The result of this research are the factors that affect significantly for students graduation based on study period are majors, sex, and duration of the thesis, while the factors that significantly for students graduation based on GPA are the entry system, duration of the thesis and the number of parents’ dependents.
PENERAPAN REGRESI LOGISTIK ORDINAL UNTUK MENGANALISIS TINGKAT KEPARAHAN KORBAN KECELAKAAN LALU LINTAS KABUPATEN BULELENG DEWA AYU MADE DWI YANTI PURNAMI; I KOMANG GDE SUKARSA; G. K. GANDHIADI
E-Jurnal Matematika Vol 4 No 2 (2015)
Publisher : Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/MTK.2015.v04.i02.p089

Abstract

Ordinal logistic regression is a statistical method for analyzing the respone variables that have an ordinal scale consisting of three or more categories. This method is an extension of logistic regression with a binary respone variable. In this study the cases studies was the severity of traffic accident victims in Buleleng. The severity of the victims were divided into three categories: minor injuries, serious injuries and died. This research also used six predictor variables, namely age, hours of accident, education, gender, the status of location, and the venicles involved. Result of study shows that the variables age, hours of accident, education and the status of location have a significan effect on the severity of traffic accident victims.
PEMODELAN RISIKO PENYAKIT PNEUMONIA PADA BALITA DI PROVINSI JAWA TIMUR DENGAN PENDEKATAN GEOGRAPHICALLY WEIGHTED LOGISTIC REGRESSION EVI NOVIYANTARI FATIMAH; I KOMANG GDE SUKARSA; MADE SUSILAWATI
E-Jurnal Matematika Vol 4 No 2 (2015)
Publisher : Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/MTK.2015.v04.i02.p085

Abstract

This research is aim to determine the comparison of logistic regression models and models Geographically Weighted Logistic Regression and the factors that significantly affect the risk of pneumonia in toddlers in East Java Province. Logistic regression is a statistical analysis that is used to describe the response variable is categorical with the independent variables are categorical or continuous. The main problem of this method if  it’s applied in data that is affected of geographic location or spatial data. One of many method to solve the spatial data is Geographically Weighted Logistic Regression (GWLR). GWLR is a statistical method for analyze the data to account for spatial factor. The results showed that there are no significant differences between the logistic regression model with GWLR model. Factors that significantly affect the risk of pneumonia in toddlers in East Java Province is the percentage of low birth weight, the percentage of  toddlers who get measles immunization, the percentage of toddlers who get vitamin A, and the percentage of toddlers who get DPT+HB immunization.
MODEL NON LINIER GARCH (NGARCH) UNTUK MENGESTIMASI NILAI VALUE at RISK (VaR) PADA IHSG I KOMANG TRY BAYU MAHENDRA; KOMANG DHARMAWAN; NI KETUT TARI TASTRAWATI
E-Jurnal Matematika Vol 4 No 2 (2015)
Publisher : Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/MTK.2015.v04.i02.p090

Abstract

In investment, risk measurement is important. One of risk measure is Value at Risk (VaR). There are many methods that can be used to estimate risk based on VaR framework. One of them Non Linier GARCH (NGARCH) model. In this research, determination of VaR used NGARCH model. NGARCH model allowed for asymetric behaviour in the volatility such that “good news” or positive return and “bad news” or negative return. Based on calculations of VaR, the higher of the confidence level and the longer the investment period, the risk was greater. Determination of VaR using NGARCH model was less than GARCH model.
KAJIAN TERHADAP TINGKAT PEMERATAAN PENDIDIKAN MENGGUNAKAN ANALISIS BIPLOT KLASIK DAN BIPLOT KEKAR NI LUH ARDILA KUSUMAYANTI; I KOMANG GDE SUKARSA; TJOKORDA BAGUS OKA; I PUTU EKA N. KENCANA
E-Jurnal Matematika Vol 4 No 2 (2015)
Publisher : Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/MTK.2015.v04.i02.p086

Abstract

The aim of this research is to find the better from classical and robust biplot in determine dominant indicators of educational equity in Bali, NTB and NTT Provinces. This research based on secondary data obtain from Central Bureau of Statistics for year 2012/2013. Educational equity was portraited by Classical and Robust Biplot. The results of this research showed Robust Biplot is better method which goodness of fit is 90,64% meanwhile Classical Biplot as much as 83,62%. The Robust Biplot showed Students- Junior or Islamic Middle School Ratio and Students-Senior or Islamic High School were dominant indicators to educational equity in Bali,  NTB and NTT Provinces.
PENENTUAN NILAI VALUE at RISK PADA SAHAM IHSG MENGGUNAKAN MODEL GEOMETRIC BROWNIAN MOTION DENGAN LOMPATAN I GEDE ARYA DUTA PRATAMA; KOMANG DHARMAWAN; LUH PUTU IDA HARINI
E-Jurnal Matematika Vol 4 No 2 (2015)
Publisher : Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/MTK.2015.v04.i02.p091

Abstract

The aim of this research was to measure the risk of the IHSG stock data using the Value at Risk (VaR). IHSG stock index data typically indicates a jump. However, Geometric Brownian Motion (GBM) model can not catch any of the jumps. To view the jumps, it is necessary that the model was then developed into a Geometric Brownian Motion (GBM) model with Jumps. On the GBM model with Jumps, returns the data are discontinuous. To determine the value of VaR, the value of return to perform the simulation model of GBM with Jumps is required. To represent processes that contain jumps, discontinuous Poisson process using the Peak-Over Threshold is required. To determine the parameters of model, calibration of historical data using the Maximum Likelihood Estimation (MLE) method is performed. VaR value for GBM model with Jumps with a 95% and 99% confidence level are -0,0580 and -0,0818 while VaR value for GBM model with a 95% and 99% confidence level are -0,0101 and -0,0199. VaR for GBM model with Jumps with a confidence level of 95% and 99% show greater than the model VaR for GBM.

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