cover
Contact Name
-
Contact Email
-
Phone
-
Journal Mail Official
-
Editorial Address
Department of Statistic, Faculty of Science and Mathematics , Universitas Diponegoro Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro Gedung F lt.3 Tembalang Semarang 50275
Location
Kota semarang,
Jawa tengah
INDONESIA
Jurnal Gaussian
Published by Universitas Diponegoro
ISSN : -     EISSN : 23392541     DOI : -
Core Subject : Education,
Jurnal Gaussian terbit 4 (empat) kali dalam setahun setiap kali periode wisuda. Jurnal ini memuat tulisan ilmiah tentang hasil-hasil penelitian, kajian ilmiah, analisis dan pemecahan permasalahan yang berkaitan dengan Statistika yang berasal dari skripsi mahasiswa S1 Departemen Statistika FSM UNDIP.
Arjuna Subject : -
Articles 733 Documents
ESTIMASI KANDUNGAN HASIL TAMBANG MENGGUNAKAN ORDINARY INDICATOR KRIGING Aldila Abid Awali; Hasbi Yasin; Rita Rahmawati
Jurnal Gaussian Vol 2, No 1 (2013): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (863.445 KB) | DOI: 10.14710/j.gauss.v2i1.2146

Abstract

Kriging is a geostatistical analysis of the data used to estimate the value that represents a no sample point based sample point in the surrounding by considering the spatial correlation in the data. Kriging is an interpolation method that generates unbiased predictions or estimations and has a minimum error. Indicator kriging is an estimation method that does not require the assumption of normality of data and can also be used to treat data that have a significant outlier. The indicator kriging that based on the principle of ordinary kriging also called ordinary indicator kriging. In this case study conducted Morowali estimated iron content in Central Sulawesi using ordinary indicator kriging method. The data used in the form of data coordinate point and iron content. The results obtained are presented probability value locations that fall within the zone of potential and non potential with the value the error variance. Based on the analysis to obtain a plot depicting the location of the entry in the zones of potential iron mine on the abscissa coordinate (7150–7210), the ordinate (54180–54540), and the depth ranges (440–500) meters and also the coordinates of the abscissa (7710–8130), the ordinate (54800–54960), and depths ranging from (327–342) meters.
PEMODELAN REGRESI RIDGE ROBUST-MM DALAM PENANGANAN MULTIKOLINIERITAS DAN PENCILAN (Studi Kasus : Faktor-Faktor yang Mempengaruhi AKB di Jawa Tengah Tahun 2017) Eka Destiyani; Rita Rahmawati; Suparti Suparti
Jurnal Gaussian Vol 8, No 1 (2019): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (608.52 KB) | DOI: 10.14710/j.gauss.v8i1.26619

Abstract

The Ordinary Least Squares (OLS) is one of the most commonly used method to estimate linear regression parameters. If multicollinearity is exist within predictor variables especially coupled with the outliers, then regression analysis with OLS is no longer used. One method that can be used to solve a multicollinearity and outliers problems is Ridge Robust-MM Regression. Ridge Robust-MM  Regression is a modification of the Ridge Regression method based on the MM-estimator of Robust Regression. The case study in this research is AKB in Central Java 2017 influenced by population dencity, the precentage of households behaving in a clean and healthy life, the number of low-weighted baby born, the number of babies who are given exclusive breastfeeding, the number of babies that receiving a neonatal visit once, and the number of babies who get health services. The result of estimation using OLS show that there is violation of multicollinearity and also the presence of outliers. Applied ridge robust-MM regression to case study proves ridge robust regression can improve parameter estimation. Based on t test at 5% significance level most of predictor variables have significant effect to variable AKB. The influence value of predictor variables to AKB is 47.68% and MSE value is 0.01538.Keywords:  Ordinary  Least  Squares  (OLS),  Multicollinearity,  Outliers,  RidgeRegression, Robust Regression, AKB.
PEMODELAN GENERAL REGRESSION NEURAL NETWORK (GRNN) PADA DATA RETURN INDEKS HARGA SAHAM EURO 50 Rezzy Eko Caraka; Hasbi Yasin; Alan Prahutama
Jurnal Gaussian Vol 4, No 2 (2015): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (813.022 KB) | DOI: 10.14710/j.gauss.v4i2.8402

Abstract

General Regression Neural Network (GRNN) merupakan salah satu model jaringan radial basis yang digunakan untuk pendekatan suatu fungsi. Model GRNN termasuk model jaringan syaraf tiruan dengan solusi yang cepat, karena tidak diperlukan iterasi yang besar pada estimasi bobot-bobotnya. Model ini memiliki arsitektur jaringan yang baku, dimana jumlah unit pada pattern layer sesuai dengan jumlah data input. Salah satu aplikasi GRNN adalah untuk memprediksi nilai return saham dari indeks Euro 50 CFD (Contract For Difference). Indeks Euro 50 CFD (Contract For Difference) digunakan sebagai patokan harga saham dari 50 perusahaan terbesar di zona Eropa. Para investor melakukan investasi di saham indeks Euro 50 CFD (Contract For Difference) dengan harapan mendapatkan kembali keuntungan yang sesuai dengan apa yang telah di investasikannya. Dengan menggunakan model GRNN diperoleh bahwa nilai RMSE dan R2 untuk data training sebesar 0,00095 dan 99,19%. Untuk data testing diperoleh nilai RMSE dan R2 sebesar 0,00725 dan 98,46%. Berdasarkan nilai prediksi return saham dua belas hari ke depan diperoleh kerugian tertinggi atau capital loss pada 15 Desember 2014 sebesar 5,583188% dan profit tertinggi atau capital gain pada tanggal 10 Desember 2014 sebesar 2,267641% Kata Kunci: GRNN, Jaringan Syaraf Tiruan, Return Saham, Indeks Euro 50, Kerugian Tertinggi, Profit Tertinggi, Prediksi
PERBANDINGAN PENDEKATAN GENERALIZED EXTREME VALUE DAN GENERALIZED PARETO DISTRIBUTION UNTUK PERHITUNGAN VALUE AT RISK PADA PORTOFOLIO SAHAM Ayu Ambarsari; Sudarno Sudarno; Tarno Tarno
Jurnal Gaussian Vol 5, No 3 (2016): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (662.495 KB) | DOI: 10.14710/j.gauss.v5i3.14692

Abstract

Stock is one of investments that used by investor but often have high risk. So we need to calculate risk assessment for single stock and portfolios. Value at Risk  (VaR) is a tool often used in measuring risk, especially in stock trading. Return stock usually has a fat tail distribution, there is usually a case of  heteroscedasticity. Time series model that used to modeling this condition is Autoregressive Conditional Heteroscedasticity / Generalized Autoregressive Conditional Heteroscedasticity. This study focused on the calculation of VaR using Block Maxima with the approach Generalized Extreme Value/GEV and Peaks Over Threshold approach Generalized Pareto Distribution/GPD. Modeling volatility models of GARCH. Share data used  in the case study is a daily closing PT. Astra International and Panin Financial period January 1st, 2010 – January 22nd,  2016. The result is ARIMA(0,1,1) GARCH(1,2) which is the best model with the smallest AIC. The amount of risk with a confidence level of 95% by GEV is 3,1613%, while the GPD is 3,2761% rupiah from current asset, in other words VaR GPD higher better than GEV.Keywords: Portfolio, Return, Value at Risk (VaR), ARCH/GARCH, Block Maxima, Peaks Over Threshold, GEV, GPD.
ANALISIS VARIAN DUA FAKTOR DALAM RANCANGAN PENGAMATAN BERULANG ( REPEATED MEASURES ) Alif Hartati; Triastuti Wuryandari; Yuciana Wilandari
Jurnal Gaussian Vol 2, No 4 (2013): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (486.267 KB) | DOI: 10.14710/j.gauss.v2i4.3779

Abstract

The experimental design is a series of tests, both using descriptive statistics and inferential statistics that aims to transform the input variables into an output which is the response of the experiment. In one study, the response sometimes observed in every experiment performed more than once at different times during the study called with Repeated Measures. Observation time as if viewed as an additional factor, resulting in a repeated measures seen as a two-factor design with split-plot patterns. Factors that attempted allocated as main plots and allocated observation time as a subplot. Step-by-step analysis to test the normality of the error, test the homogeneity of variance, determine the degrees of freedom, sum of squares and mean squares of each factor. The next hypothesis to test for factor a, factor b and interaction affect both whether the observed response. If any effect, it is necessary to further test the Duncan test. The data used are secondary data on the effect of temperature, time of observation and interaction both the amylase enzyme produced by the bacterium bacillus subtilis. Results obtained by the analysis of temperature, time of observation and interaction both significantly influence the observed response.
PENGUKURAN PROBABILITAS KEBANGKRUTAN OBLIGASI KORPORASI DENGAN SUKU BUNGA COX INGERSOLL ROSS MODEL MERTON (Studi Kasus Obligasi PT Indosat, Tbk) Muhammad Akhir Siregar; Mustafid Mustafid; Rukun Santoso
Jurnal Gaussian Vol 7, No 2 (2018): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (589.236 KB) | DOI: 10.14710/j.gauss.v7i2.26652

Abstract

Nowadays bonds become one of the many securities products that are being prefered by investors. Observing the level of the company's rating which good enough or in the criteria of investment grade can’t be a handle of investors. Investing in long-term period investors should understand the risks to be faced, one of investment credit risk on bonds is default risk, this risk is related to the possibility that the issuer fails to fulfill its obligations to the investor in due date. The measurement of the probability of default failure by the structural method approach introduced first by Black-Scholes (1973) than developed by Merton (1974).  In Bankruptcy model, merton’s model assumed the company get default (bankrupt) when the company can’t pay the coupon or face value in the due date. Interest rates on the Merton model assumed to be constant values replaced by Cox Ingersoll Ross (CIR) rates. The CIR rate is the fluctuating interest rate in each period and the change is a stochastic process. The empirical study was conducted on PT Indosat, Tbk's bonds issued in 2017 with a face value of 511 Billion in payment of obligations by the issuer for 10 years. Based on simulation results done with R software obtained probability of default value equal to 7,416132E-215 Indicates that PT Indosat Tbk is deemed to be able to fulfill its obligation payment at the end of the bond maturity in 2027. Keywords: Bond, CIR Rate, Merton Model, Ekuity, Probability of default
PENENTUAN MODEL ANTRIAN DAN PENGUKURAN KINERJA PELAYANAN PLASA TELKOM PAHLAWAN SEMARANG Ilham Indra Bakti Al-Irsyad; Sugito Sugito; Hasbi Yasin
Jurnal Gaussian Vol 4, No 3 (2015): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (694.171 KB) | DOI: 10.14710/j.gauss.v4i3.9433

Abstract

Plasa Telkom Pahlawan is a place of ministry-owned PT Telkom provided to serve customers of Telkom. To serve its customers, Plasa Telkom Pahlawan operates several kind of services, they are Customer Service, Cashier, Quick Service, Sales and in November 2014 operated new kind of service, it was Flexi Upgrade. As a provider of facility services, the problem of queues is a problem that is absolutely the case and must be considered. Queue situation occurs because the number of customers at a facility of service exceed the capacity available to perform such services. At Plasa Telkom Pahlawan queuing occurs in five different  kinds of services. The best queueing models in Customer Service is (M/G/6):(GD:∞:∞) based on simulation level of aspiration, while the best model of Cashier and Quick Service are (M/M/2):(GD:∞:∞), for Sales is (M/M/1):(GD:∞:∞). Especially for Flexi Upgrade, the best model based on simulation level of aspiration is (G/G/6):(GD:∞:∞). From the analyzed model can be concluded that the queueing system available in Plasa Telkom Pahlawan Service is optimal.Keywords : Queuing system, Plasa Telkom Pahlawan, Customer Service, Cashier, Quick Service, Sales, Flexi Upgrade.
PEMODELAN DAN PERAMALAN INDEKS HARGA SAHAM GABUNGAN (IHSG), JAKARTA ISLAMIC INDEX (JII), DAN HARGA MINYAK DUNIA BRENT CRUDE OIL MENGGUNAKAN METODE VECTOR AUTOREGRESSIVE EXOGENOUS (VARX) Nunung Hanurowati; Moch. Abdul Mukid; Alan Prahutama
Jurnal Gaussian Vol 5, No 4 (2016): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (664.021 KB) | DOI: 10.14710/j.gauss.v5i4.14725

Abstract

Index of stocks listed on the Indonesia Stock Exchange (IDX) there are conventional that one of them is the Composite Stock Price Index (CSPI) and the index of stocks that are sharia is the Jakarta Islamic Index (JII). In its movement, the value of CSPI and JII often increases and decreases that are influenced by several factors, one of which is the world oil price of Brent Crude Oil. To see the value of CSPI and JII conditions during the period of the next few months it takes the model equations. Because the third such data included in the time series data, we used time series analysis with the appropriate method is the Vector Autoregressive Exogenous (VARX). VARX(p,q) is a model of multivariate time series that consists of several endogenous variable of the time series order p with q adding exogenous variables. The purpose of this study is to obtain an appropriate VARX models and forecasting for data CSPI and JII. The model to predict CSPI and JII with exogenous variables that influence the world oil prices of Brent Crude Oil is VARX(1,1). Test parameters for exogenous variables in the model VARX(1,1) not significant at significance level α = 5%, but this result could be ignored and continues to testing residual assumptions. Residual model VARX(1,1) satisfies the assumption of white noise and multivariate normal distribution, in order to obtain results as very good forecast that with each MAPE value for CSPI and JII forecast of 2,71% and 3,63%. Keywords: CPSI, JII, Brent Crude Oil, VARX, MAPE.
ANALISIS SISTEM ANTRIAN PESAWAT TERBANG DI BANDARA INTERNASIONAL AHMAD YANI SEMARANG Anggit Ratnakusuma; Abdul Hoyyi; Sugito Sugito
Jurnal Gaussian Vol 4, No 4 (2015): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (527.673 KB) | DOI: 10.14710/j.gauss.v4i4.10126

Abstract

Long queuing is not expected by anyone, because it’s taking much time and tiresome. However, this situation is not avoidable in public area, for example Ahmad Yani International Airport Semarang. Aircraft queuing that will take off and landed resulted in increasing of the queuing of passengers to aboard. The suitable queuing system model for Ahmad Yani Internasional Airport Semarang to solve its air traffic is using (M/M/6):(GD/∞/∞), with six aprons as server of reguler commercial flight. Moreover, based on the result of system performance measure, service system in Ahmad Yani Internasional Airport Semarang report is good enough. The result of system performance measure said that average number of aircraft in the system (Ls) was 1,0716 aircraft per hour, average number of aircraft in the queue (Lq) was 0,0002 aircraft per hour, average time aircraft spends in the system (Ws) was 0,4977 from an hour, and average time aircraft spends in the queue (Wq) was 0,0001 from an hour. The simulation showed that by using four operating server or adding two more arrival additionals in every hour, the service system is quite effective. Keywords: Queuing System Model, Ahmad Yani International Airport Semarang
PENENTUAN FAKTOR PRIORITAS MAHASISWA DALAM MEMILIH TELEPON SELULER MERK BLACKBERRY DENGAN FUZZY AHP Shega, Hanien Nia H; Rahmawati, Rita; Yasin, Hasbi
Jurnal Gaussian Vol 1, No 1 (2012): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (569.133 KB) | DOI: 10.14710/j.gauss.v1i1.575

Abstract

This study aims to determine the priority factor Diponegoro University students in choosing a BlackBerry mobile phone brands. Consumer or buyer is often confused in making the decision to buy a product because of the many factors that affect the choices available. From the method of Analytic Hierarchy Process (AHP) was found to be too subjective assessment of uncertainty for qualitative data. The problems above can be solved by the method of Fuzzy Analytic Hierarchy Process (FAHP), which uses the interval so that the assessment of qualitative data can provide a more objective assessment. The criteria used to be in this research are quality, price, design, and service. The data were taken by spreading questionnaires. From the answer of respondent, calculation of ratio was performed with a consistency ratio (CR). If CR<0.10 it means the answer of respondent is consisten and can be used for Fuzzy AHP. Based on the result of research, it could be concluded that quality was the top priority with 0.278 priority weights, then the service with 0.254 priority weights, design with 0.240 priority weight, and price with 0.228 priority weights.

Filter by Year

2012 2024


Filter By Issues
All Issue Vol 13, No 1 (2024): Jurnal Gaussian Vol 12, No 4 (2023): Jurnal Gaussian Vol 12, No 3 (2023): Jurnal Gaussian Vol 12, No 2 (2023): Jurnal Gaussian Vol 12, No 1 (2023): Jurnal Gaussian Vol 11, No 4 (2022): Jurnal Gaussian Vol 11, No 3 (2022): Jurnal Gaussian Vol 11, No 2 (2022): Jurnal Gaussian Vol 11, No 1 (2022): Jurnal Gaussian Vol 10, No 4 (2021): Jurnal Gaussian Vol 10, No 3 (2021): Jurnal Gaussian Vol 10, No 2 (2021): Jurnal Gaussian Vol 10, No 1 (2021): Jurnal Gaussian Vol 9, No 4 (2020): Jurnal Gaussian Vol 9, No 3 (2020): Jurnal Gaussian Vol 9, No 2 (2020): Jurnal Gaussian Vol 9, No 1 (2020): Jurnal Gaussian Vol 8, No 4 (2019): Jurnal Gaussian Vol 8, No 3 (2019): Jurnal Gaussian Vol 8, No 2 (2019): Jurnal Gaussian Vol 8, No 1 (2019): Jurnal Gaussian Vol 7, No 4 (2018): Jurnal Gaussian Vol 7, No 3 (2018): Jurnal Gaussian Vol 7, No 2 (2018): Jurnal Gaussian Vol 7, No 1 (2018): Jurnal Gaussian Vol 6, No 4 (2017): Jurnal Gaussian Vol 6, No 3 (2017): Jurnal Gaussian Vol 6, No 2 (2017): Jurnal Gaussian Vol 6, No 1 (2017): Jurnal Gaussian Vol 5, No 4 (2016): Jurnal Gaussian Vol 5, No 3 (2016): Jurnal Gaussian Vol 5, No 2 (2016): Jurnal Gaussian Vol 5, No 1 (2016): Jurnal Gaussian Vol 4, No 4 (2015): Jurnal Gaussian Vol 4, No 3 (2015): Jurnal Gaussian Vol 4, No 2 (2015): Jurnal Gaussian Vol 4, No 1 (2015): Jurnal Gaussian Vol 3, No 4 (2014): Jurnal Gaussian Vol 3, No 3 (2014): Jurnal Gaussian Vol 3, No 2 (2014): Jurnal Gaussian Vol 3, No 1 (2014): Jurnal Gaussian Vol 2, No 4 (2013): Jurnal Gaussian Vol 2, No 3 (2013): Jurnal Gaussian Vol 2, No 2 (2013): Jurnal Gaussian Vol 2, No 1 (2013): Jurnal Gaussian Vol 1, No 1 (2012): Jurnal Gaussian More Issue