Jurnal Gaussian
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.
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<![CDATA[REGRESI SPLINE SEBAGAI ALTERNATIF DALAM PEMODELAN KURS RUPIAH TERHADAP DOLAR AMERIKA SERIKAT ]]>
<![CDATA[Sulton Syafii Katijaya]]>;
<![CDATA[Suparti Suparti]]>;
<![CDATA[Sudarno Sudarno]]>
<![CDATA[ Jurnal Gaussian Vol 2, No 3 (2013): Jurnal Gaussian ]]>
Publisher : <![CDATA[Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro ]]>
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DOI: 10.14710/j.gauss.v2i3.3668
<![CDATA[Exchange rate is the ratio of value or price of the currency between two countries. Many factors are thought to affect change in the inflation rate, the activity balance of payments, interest rate differentials, the relative level of income, government control and expectations. Therefore the method that can be used to analyze the exchange rate is needed such as the classical time series analysis (parametric). However the fluctuated data rate doesn’t occupy the assumption of stationarity often. Another alternative for this study is the spline regression. Spline is a nonparametric regression that doesn’t hold any assumption of regression curves. Spline regression has high flexibility and ability to estimate the data behavior which is likely to be different at every point of the interval, with the help of knots. The best model depends on the determination of the optimal point knots, that is has a minimum value of Generalized Cross Validation (GCV). Using data daily exchange rate of the rupiah against the dollar in the period of January 2, 2012 until October 15, 2012, the best spline model in this study is when using 2 to 3 order of approaching knots point, those points are 9512, 9517 and 9522 with the GCV = 1036.38.]]>
<![CDATA[KAJIAN AVAILABILITAS PADA SISTEM KOMPONEN SERI ]]>
<![CDATA[Avida Nugraheni C.]]>;
<![CDATA[Sudarno Sudarno]]>;
<![CDATA[Triastuti Wuryandari]]>
<![CDATA[ Jurnal Gaussian Vol 2, No 3 (2013): Jurnal Gaussian ]]>
Publisher : <![CDATA[Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro ]]>
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DOI: 10.14710/j.gauss.v2i3.3664
<![CDATA[Availability is a measure of system performance and measures the combined effect of reliability, maintenance and logistic support on the operational effectiveness of the system. Availability of series system is derived from inherent availability of system that takes effect from mean time to failure (MTTF) and mean time to repair (MTTR). Given observed time data of microcontroller consists of processor core, memory and programmable I/O peripheral in series, is measured its system availability. By simple linier regression method, the parameter estimation is determined after data distribution known, for the mean time. Processor core has Weibull distribution for failure time data with , and as regression model while repair time data is lognormal distribution with , and regression model is . Memory has exponential failure time data with and as regression model while normal repair time data has dan and regression model is . Failure time data distribution of programmable I/O peripherals is Weibull with , and regression model while lognormal repair time data has , and regression model is . Due to MTTF is 11364.57 hours and MTTR is 41.59 hours, processor core’s availability is 99.64%. Availability of memory is 99.87% from MTTF is 20000 hours and MTTR is 27 hours. Programmable I/O peripheral has 18773.41 hours as MTTF and MTTR is 38.67 hours that deliver availability 99.79%. The series system availability is 99.30% means the probability of system is in the state of functioning at given time is 99.30%.]]>
<![CDATA[PREDIKSI CURAH HUJAN DENGAN METODE KALMAN FILTER (Studi Kasus di Kota Semarang Tahun 2012) ]]>
<![CDATA[Tika Dhiyani Mirawati]]>;
<![CDATA[Hasbi Yasin]]>;
<![CDATA[Agus Rusgiyono]]>
<![CDATA[ Jurnal Gaussian Vol 2, No 3 (2013): Jurnal Gaussian ]]>
Publisher : <![CDATA[Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro ]]>
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DOI: 10.14710/j.gauss.v2i3.3669
<![CDATA[The rainfall data is very interesting to be studied because it is constitutes one of the biggest factor that influence the climate on a region and human life sector. In this studies, the rainfall prediction is utilized by Kalman Filter method. The implementation of Kalman Filter analysis in this research is used for modelling and forecasting rainfall in Semarang city. This method provide a recursive solution to minimize error. Kalman Filter consists of state equation and observation equation. The forecasting result in 2012 showed that the prediction is close to the current data whereas in 2013 it increase which the maximum rainfall is 406 mm happening in February and the minimum rainfall is 35 mm happening in July. Overall, the average rainfall in 2013 at Semarang city is 196,25 mm]]>
<![CDATA[PENGUKURAN RISIKO KREDIT OBLIGASI KORPORASI DENGAN CREDIT VALUE AT RISK (CVAR) DAN OPTIMALISASI PORTOFOLIO MENGGUNAKAN METODE MEAN VARIANCE EFFICIENT PORTFOLIO (MVEP) ]]>
<![CDATA[Agus Somantri]]>;
<![CDATA[Di Asih I Maruddani]]>;
<![CDATA[Abdul Hoyyi]]>
<![CDATA[ Jurnal Gaussian Vol 2, No 3 (2013): Jurnal Gaussian ]]>
Publisher : <![CDATA[Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro ]]>
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DOI: 10.14710/j.gauss.v2i3.3660
<![CDATA[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.]]>
<![CDATA[PERBANDINGAN ARIMA DENGAN FUZZY AUTOREGRESSIVE (FAR) DALAM PERAMALAN INTERVAL HARGA PENUTUPAN SAHAM (Studi Kasus pada Jakarta Composite Index) ]]>
<![CDATA[Muhammad Fitri Lutfi Anshari]]>;
<![CDATA[Dwi Ispriyanti]]>;
<![CDATA[Yuciana Wilandari]]>
<![CDATA[ Jurnal Gaussian Vol 2, No 3 (2013): Jurnal Gaussian ]]>
Publisher : <![CDATA[Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro ]]>
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DOI: 10.14710/j.gauss.v2i3.3665
<![CDATA[The capital market is one of the most popular investment option today. In capital market, stock price prediction is an important issue for investors, so needed a good forecasting method as a basic for decision-making for the transaction. One of the most popular forecasting method is ARIMA, but this method still uses the concept that measurement error which is obtained from the difference between the observed values with estimated values. To resolve the error in modeling, Fuzzy Autoregressive was developed, it is a model combination of Fuzzy Regression and Autoregressive (AR). This method gives results in interval forecasting, thus providing information to decision makers regarding the best and worst situation that may occur. This paper discusses the application of Fuzzy Autoregressive forecasting interval for the Jakarta Composite Index and compare it with the ARIMA prediction interval. The result of this study is Fuzzy Autoregressive interval is narrower than the ARIMA 95% significance rate]]>
<![CDATA[PENENTUAN TREN ARAH PERGERAKAN HARGA SAHAM DENGAN MENGGUNAKAN MOVING AVERAGE CONVERGENCE DIVERGENCE (Studi Kasus Harga Saham pada 6 Anggota LQ 45) ]]>
<![CDATA[Tri Murda Agus Raditya]]>;
<![CDATA[Tarno Tarno]]>;
<![CDATA[Triastuti Wuryandari]]>
<![CDATA[ Jurnal Gaussian Vol 2, No 3 (2013): Jurnal Gaussian ]]>
Publisher : <![CDATA[Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro ]]>
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DOI: 10.14710/j.gauss.v2i3.3670
<![CDATA[One of many examples of technical indicator that frequently used for stock price analysis is Moving Average Convergence Divergence (MACD). MACD generates two signal called goldencross and deathcross are used to find the reversal momentum of stock price trend movement. Goldencross as a oversold point marker serves to give a buying signal. While, deathcross as a overbought point marker serves to give a selling signal. Research on six stocks member of LQ45 (ANTM, BWPT, MNCN, TINS, BJBR, and LPKR) during the period January 1 until October 31, 2012 managed to prove the accuracy of the signal formed by MACD signal. By applying the MACD Indicator consistently, investors can get a percentage of profit above the actual inflation rate in 2012 by Indonesian Bank. On these results, the goldencross and deathcross signal give a good performance as tool of technical analysis for determining the trend of the direction of stock price movements]]>
<![CDATA[PERBANDINGAN ANALISIS DISKRIMINAN LINIER KLASIK DAN ANALISIS DISKRIMINAN LINIER ROBUST UNTUK PENGKLASIFIKASIAN KESEJAHTERAAN MASYARAKAT KABUPATEN/KOTA DI JAWA TENGAH ]]>
<![CDATA[Kartikawati, Ana]]>;
<![CDATA[Mukid, Moch. Abdul]]>;
<![CDATA[Ispriyanti, Dwi]]>
<![CDATA[ Jurnal Gaussian Vol 2, No 3 (2013): Jurnal Gaussian ]]>
Publisher : <![CDATA[Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro ]]>
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DOI: 10.14710/j.gauss.v2i3.3661
<![CDATA[Discriminant analysis is a statistics method which is used to classify an individual or object into certain group which has determined based on its independent variables. Discriminant analysis that commonly used is classical discriminant analysis which consist of classical linear discriminant analysis and classical quadratic discriminant analysis. In classical linear discriminant analysis there are two assumptions to be fulfilled i.e. independent variables have to be normal multivariate distributed and the covariance matrix from the two observed objects should be the same. Classical discriminant analysis cannot work properly if the data which being analyzed consists of many outliers. In order to make discriminant analysis works optimally within the classification though in the condition of data which contains of many outliers, robust estimator is needed. The robust discriminant analysis is used to get the high classification accuracy for data which contains of many outliers. Fast-MCD estimator is one of the robust estimators which is aimed to get the smallest determinant of covariance matrices. The robust linear discriminant analysis with fast-MCD method in this graduating paper is implemented to determine the prosperity status of the people in the regencies or towns in Central Java. The total proportion of classification accuracy using robust linear discriminant analysis method on the data of Central Java people prosperity is 77.14 percent. It is equal with the result from classic linear discriminant analysis which is also 77.14 percent. It is caused by the few amount of outlier on the data of Central Java people prosperity.]]>
<![CDATA[PENGAMBILAN SAMPEL BERDASARKAN PERINGKAT PADA ANALISIS REGRESI LINIER SEDERHANA ]]>
<![CDATA[Wijayanti, Pritha Sekar]]>;
<![CDATA[Ispriyanti, Dwi]]>;
<![CDATA[Wuryandari, Triastuti]]>
<![CDATA[ Jurnal Gaussian Vol 2, No 3 (2013): Jurnal Gaussian ]]>
Publisher : <![CDATA[Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro ]]>
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DOI: 10.14710/j.gauss.v2i3.3666
<![CDATA[Ranked Set Sampling and Ranked Set Sampling concomitant are more efficient than Simple Random Sampling. This can be determined by calculating the Relative Precision which is a ratio value from the variance of the mean from each sampling technique. From the research of Ranked Set Sampling, obtained , and so Ranked Set Sampling is more efficient than Simple Random Sampling. For the research of Ranked Set Sampling concomitant, obtained , and so Ranked Set Sampling concomitant is more efficient than Simple Random Sampling, and for simple linear regression analysis obtained , , , so simple linear regression model of Ranked Set Sampling is more efficient than simple linear regression model of Simple Random Sampling]]>
<![CDATA[PERBANDINGAN MODEL REGRESI BINOMIAL NEGATIF DENGAN MODEL GEOGRAPHICALLY WEIGHTED POISSON REGRESSION (GWPR) (Studi kasus : Angka Kematian Ibu di Provinsi Jawa Timur Tahun 2011) ]]>
<![CDATA[M. Ali Ma'sum]]>;
<![CDATA[Suparti Suparti]]>;
<![CDATA[Dwi Ispriyanti]]>
<![CDATA[ Jurnal Gaussian Vol 2, No 3 (2013): Jurnal Gaussian ]]>
Publisher : <![CDATA[Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro ]]>
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DOI: 10.14710/j.gauss.v2i3.3671
<![CDATA[Maternal mortality rate is one of the crucial problems of death in Indonesia. Maternal deaths in East Java province is likely to increase so that the role of data and information are very important. Negative Binomial Regression is a model that can be used to address the problem overdispersion. While the method of spatial attention factor for type discrete data is Geographically Weighted Poisson Regression Model (GWPR). This study was conducted on the comparison between the Negative Binomial Regression and GWPR to discuss the factors that influence maternal mortality rate in the province of East Java. Indicators that affect maternal mortality include maternal health services. Maternal health services such as antenatal care, obstetric complications treated, Aid deliveries by skilled health care child birth, and neonatal health care services handled neonatal complications. The results of testing the suitability of model shows that there is no influence of spatial factors on maternal mortality rate in the province of East Java. Based on Negative Binomial Regression derived variable number of puerperal women who received vitamin A significantly affect maternal mortality rate, while for GWPR is divided into six clusters districts/cities by same significant variables. From the comparison value of AIC was found that GWPR better to analyzing Maternal mortality in East Java because it has the smallest value of AIC]]>
<![CDATA[PEMETAAN PERSEPSI MERK LAPTOP DI KALANGAN MAHASISWA MENGGUNAKAN ANALISIS KORESPONDENSI BERGANDA (Studi kasus: Mahasiswa Universitas Diponegoro Semarang) ]]>
<![CDATA[Anissa Pangastuti]]>;
<![CDATA[Moch. Abdul Mukid]]>;
<![CDATA[Sudarno Sudarno]]>
<![CDATA[ Jurnal Gaussian Vol 2, No 3 (2013): Jurnal Gaussian ]]>
Publisher : <![CDATA[Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro ]]>
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DOI: 10.14710/j.gauss.v2i3.3662
<![CDATA[The growth of technology makes producer compete creating sophisticated, modern, and practical tools. One of them is competing creating notebook. Some brands that more develop than other brands in the market are Toshiba, Acer, Asus, HP and Dell. This research studies about positioning one brand against other brands in the market and proximity between all brands that affected by some factors. There are, processors, designation notebook for consumer, features, endorsement and guarantee, endurance notebook against damage, and the distant age of notebook consumption when it has damage in hardware for the first time. Because there are so many factors that affecting perceptual mapping and positioning notebook at the market, hence it need to be analyzed using multiple correspondence analysis. Multiple correspondence analysis is an expansion technique from simple correspondence analysis which is a multivariate technique graphically used for exploration data from a multi-way contingency table. The result of this research makes conclusion that there is a similarity between Acer and HP notebook. This statement be marked with proximity of point Acer and HP. It can be seen from the incision magnitude between both of that brands. There are both of them be used for graphic and designing, have the same complete features and for time of damage for the first time that both of that brands experienced are at age > 3 years]]>
