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Jurnal Gaussian

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Published by Universitas Diponegoro

ISSN : - EISSN : 23392541 DOI : -

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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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Articles 36 Documents

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Search results for , issue "Vol 3, No 4 (2014): Jurnal Gaussian" : 36 Documents clear

Peramalan Laju Inflasi dan Nilai Tukar Rupiah Terhadap Dolar Amerika Menggunakan Model Vector Autoregressive (VAR) Fitrian Fariz Ichsandi; Rita Rahmawati; Yuciana Wilandari
Jurnal Gaussian Vol 3, No 4 (2014): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Vector Autoregressive Method (VAR) is a simultaneous equation model has several endogeneous variables. In the VAR Model each variable endogeneous is explained by lag from own value and lag from the other variable. Equation of VAR generally use to forecast. In this final task VAR model was applied to find the forecasting value of inflation rate in Indonesia and the US dollar exchange rates. Testing in VAR models includes stationarity test, granger causality test and white noise test. Based on the analysis showed that inflation variable and US dollar exchange rates variable are both experiencing differencing first lag so as mentions for both variables become d_inflasi and d_kurs. The best lag for VAR model is lag 3 for each model. Forecasting for 5 periods refers to indicate that inflation rate fluctuated is stable at the average rate 0,33% while the US dollar exchange rates tended to decrease on 4 periode and increase on periode to 5 with an average exchange rate is Rp. 10.018,76.Keywords: inflation, US dollar exchange rates, VAR

PERBANDINGAN METODE VARIANCE COVARIANCE DAN HISTORICAL SIMULATION UNTUK MENGUKUR RISIKO INVESTASI REKSA DANA Bayu Heryadi Wicaksono; Yuciana Wilandari; Agus Rusgiyono
Jurnal Gaussian Vol 3, No 4 (2014): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

One of the instruments of financial assets are investments in mutual funds. Every day of the total fair value of the assets in the mutual fund is always changing because the market value of each type of asset that is changing. Thus causing mutual fund has a risk. It is necessary for the measurement of risk in mutual funds using the Value at Risk (VaR). There are three methods of calculating the VaR Variance-covariance method, Monte Carlo simulation methods and methods Historical Simulation. In this study, the variance-covariance method used and the Historical Simulation method to measure potential losses on investments largest mutual fund shares at 95% confidence level. The test used is the Kolmogorov-Smirnov normality test and Kupiec test return data to test the accuracy of the calculation of VaR. Because the data are not normally distributed returns, the adjustment is then performed using the Cornish-Fisher Expansion. By using the t test results show that the calculation of VaR with variance-covariance and Historical Simulation did not differ significantly. The test results show that the accuracy of the VaR VaR accurately all used to measure the magnitude of the maximum potential loss on investments in mutual fund shares. Keywords : Value at Risk (VaR), Variance-covariance, Historical Simulation, Mutual Fund, Risk.

PENERAPAN METODE KLASIFIKASI SUPPORT VECTOR MACHINE (SVM) PADA DATA AKREDITASI SEKOLAH DASAR (SD) DI KABUPATEN MAGELANG Octaviani, Pusphita Anna; Wilandari, Yuciana; Ispriyanti, Dwi
Jurnal Gaussian Vol 3, No 4 (2014): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Accreditation is the recognition of an educational institution given by a competent authority, that is Badan Akreditasi Nasional Sekolah/Madrasah (BAN - S/M) after it is assessed that the institution has met the eight components of the accreditation assessment. An elementary school, as one of the compulsory basic education, should have the status of accreditation to ensure the quality of education. This study aimed to apply the classification method Support Vector Machine (SVM) on the data accreditation SD in Magelang. Support Vector Machine (SVM) is a method that can be used as a predictive classification by using the concept of searching hyperplane (separator functions) that can separate the data according to the class. SVM using the kernel trick for non-linear problems which can transform data into a high dimensional space using a kernel function, so that the data can be classified linearly. The results of this study indicate that the prediction accuracy of SVM classification using Gaussian kernel function RBF is 93.902%. It is calculated from 77 of 82 elementary schools that are classified correctly with the original classes. Keywords : Accreditation, Classification, Support Vector Machine (SVM), hyperplane, Gaussian RBF Kernel, Accuracy

ANALISIS SISTEM ANTREAN PELAYANAN DI KANTOR PERTANAHAN KOTA SEMARANG Lenti Agustina Lianasari Tambunan; Sugito Sugito; Hasbi Yasin
Jurnal Gaussian Vol 3, No 4 (2014): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Kantor Pertanahan Kota Semarang in charge of the land with an area of 373.70 km2 coverage, every day crowded with visitors who want to take care of the land petition. However, the high number of applicants who must be served not proportional to the number of care facilities available to the applicant should enter the waiting list queue or experiencing situation. This situation occurs in almost all counters, namely Counter 1 Land Information, Counter 2 Registration, Counter 3 Payment, and Counter 4 Product Delivery. Therefore, the required analysis is based on the model line system in accordance with the conditions of service which can then be used to address the issue queue. Based on the analysis, the model system is the best line in counter 1 land information (M/M/1): (GD/∞/∞). Counter 2 registration which is divided into 7 sub-counters have a model (M/M/2): (GD/∞/∞) to sub counters 2A, 2B, 2C, 2E/F, 2G, 2H, and the model (M/M/4): (GD/∞/∞) to sub counter 2D. Counter 3 payment (M/M/2): (GD/∞/∞). Counter 4 is the product delivery (M/M/2): (GD/∞/∞).Keywords : Queuing system, Service, Arrivals

PERHITUNGAN VALUE AT RISK MENGGUNAKAN MODEL INTEGRATED GENERALIZED AUTOREGRESSIVE CONDITIONAL HETEROSCEDASTICITY (IGARCH) (Studi Kasus pada Return Kurs Rupiah terhadap Dollar Australia) Dian Febriana; Tarno Tarno; Sugito Sugito
Jurnal Gaussian Vol 3, No 4 (2014): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Foreign exchange trading can be an alternative investment due to the rapid movement of the exchange rate and its liquid characteristic. Measurement of risk is important because investment is related to substantial funds. One of the popular methods of risk measurement is Value at Risk (VaR) method. In financial time series, data usually have a variance that is not constant (heteroscedastisity). To overcome these problems, ARCH and GARCH models are used. One type of ARCH / GARCH namely Integrated Generalized Autoregressive Conditional Heteroscedasticity (IGARCH). The purpose of this study is modeling the IGARCH volatility and to calculate VaR based on the estimate volatility of the exchange rate return data rupiah against the Australian dollar. This study use daily selling rate data of the rupiah against the Australian dollar from 1 June 2012 until February 28, 2014. The best IGARCH model used for forecasting volatility of exchange rate return data Rupiah against the Australian dollar is the ARIMA model ([10], 0, [19]) IGARCH (1,1) because it has the smallest AIC value. The estimation volatility forecasting results obtained from the IGARCH (1,1) is used to calculate the value at risk on 5 periods ahead with one day holding period and a confidence level of 95%. Value at Risk to be around 0.95% to 1.07% with the highest VaR on 3rd March 2014 and the lowest VaR on 7th March 2014. Keywords : Exchange rate, Volatility, Integrated Generalized Autoregressive Conditional Heteroscedasticity (IGARCH), Value at Risk (VaR)

ANALISIS FAKTOR-FAKTOR YANG MEMPENGARUHI KEPUASAN MAHASISWA DALAM PEMILIHAN JURUSAN MENGGUNAKAN STRUCTURAL EQUATION MODELING (SEM) (Studi Kasus di Jurusan Statistika Universitas Diponegoro Semarang) Allima Stefiana Insani; Abdul Hoyyi; Rita Rahmawati
Jurnal Gaussian Vol 3, No 4 (2014): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

University is an institution that provide educational service which has a wide variety of majors. Image of the university would affect the interest of new students in decision making process, as this will affect student satisfaction through the course. Many factors influence students decision in determining their aim majors, such as service quality, curriculum, environment and academic ability. These factors are latent variables then Structural Equation Modeling (SEM) used to determine factors effect that affect student satisfaction in selection of majors. The research conducted at Diponegoro University in Statistics Department. Overall model fit test obtain Goodness Of Fit on model with the value of GFI = 0,875 and RMSEA = 0,084 are indicative of a good fit. In concluding the analysis, the factors that affect student satisfaction in decision to choose Statistics Department can be measured by academic ability, curriculum, and service quality. Students decision in choosing Statistics Department can be explained by the academic ability of students, the curriculum which is owned by Statistics Department and quality of service that is owned by the department of statistics at 96,9%. Statistics students satisfaction can be explained by academic ability of students and student decision after choosing Statistics Department of 68,8%. Key words: Decision in choosing major, students satisfaction, Structural Equation Modeling

PENGUKURAN KINERJA PORTOFOLIO SAHAM MENGGUNAKAN MODEL BLACK-LITTERMAN BERDASARKAN INDEKS TREYNOR, INDEKS SHARPE, DAN INDEKS JENSEN (Studi Kasus Saham-Saham yang Termasuk dalam Jakarta Islamic Index Periode 2009-2013) Siti Azizah; Sugito Sugito; Alan Prahutama
Jurnal Gaussian Vol 3, No 4 (2014): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

The composing of portfolio is one of the way to minimize the risk of investment. Through portfolio, it is expected that some stocks still give return when other stocks are loss. From this composed portfolio, every investor expect appropriate return. The higher the return is better. Black-Litterman Model is the method which optimize the investor’s return by giving difference financial capital proportion for every stocks of portfolio. This method combines both the aspect historical data and the investor view to make new prediction about return of portfolio as the basic to compose the weight model of assets. Investor often compose some portfolio to plan their investment, to compare the performance (capability to produce return and also risk) from any number of portfolio, before evaluating whether the performance of chosen portfolio has been appropriate with the expectation. The measurement of the performance of portfolio is done by using Sharpe, Treynor, and Jensen Indeks. The result of the case study of eleven Jakarta Islamic Indexstocks in the period of 2009-2013 recommend the portfolio with the best perform, whichis optimized which Black-Litterman Model. Based on Sharpe Indeks, the best portfolio consists of SMGR 60,79% and INTP 39,21% of capital allocation. Based on Treynor and Jensen Indeks, the best portfolio consists of SMGR 22,59%, INTP 37,67%, PTBA 1,62%, ANTM 2,69%, ITMG 16,17%, and KLBF 19,26%. Keywords : JII, Portfolio, Black-Litterman Model, Treynor Index, Sharpe Index, Jensen Index.

PEMODELAN INDEKS HARGA SAHAM GABUNGAN (IHSG) MENGGUNAKAN MULTIVARIATE ADAPTIVE REGRESSION SPLINES (MARS) Ndaru Dian Darmawanti; Suparti Suparti; Diah Safitri
Jurnal Gaussian Vol 3, No 4 (2014): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Composite Stock Price Index (CSPI) is a historical information about the movement of joint-stock until a certain date. CSPI is often used by inventors to see a representation of the overall stock price, it can analyze the possibility of increase or decrease in stock price. Following old examination, some economy macro variables affecting CSPI is inflation, interest rate,and exchange rate the Rupiah againts the u.s.dollar. MARS method is particularly suitable to analyze a CSPI because many variables that affected. Furthermore, in the real world is very difficult to find a spesific data pattern. The analysis is MARS analysis. The purpose is an obtained a MARS model to be used to analyze the CSPI movement’s. Selection MARS model can be used CV method. The MARS model is an obtained from combination of BF, MI, dan MO. In this case, happens the best models with BF=9, MI=2, dan MO=1. Accuracy for MARS model can see MAPE values is 14,32588% it means the model can be used.Keyword: CSPI, economy macro, MARS, CV, MAPE.

DIAGRAM KONTROL MULTIVARIAT BERDASARKAN JARAK CHI-KUADRAT UNTUK QUALITY CONTROL PRODUKSI DI PT ARA SHOES Galuh Ayu Prameshti; Sudarno Sudarno; Diah Safitri
Jurnal Gaussian Vol 3, No 4 (2014): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Shoes are demands required by everyone. As a time changing and increasing demand for shoes, so many competitor shoe factories produce the best shoes for the customer. PT Ara Shoes is a famous shoe factory that has been well known for six decades. To be able to make fairness quality competition shoe factory would have to ability to produce a high quality product. To improve quality and production process is the way to determine whether quality of production is already achieve the minimum standard quality needed by applying the minimum standard quality control system. Control charts based on chi-square distance is a diagram of the control that can be used for multivariate data attributes. Production processes at PT ARA Shoes is divided into 3 stages of the shoe production process, including the process of cutting, process of sewing and assembling process. The cases study examined in this observation is the production process of cutting from January 2012 - October 2013 total applying 22 observations. Based on the research that has been done it is concluded that the production process is not enough controlled in cutting and improvement needed to be done twice, by eliminating observations 4th and 5th.Keywords : shoes charts control, chi-square distance, PT ARA Shoes

IDENTIFIKASI LAMA STUDI BERDASARKAN KARAKTERISTIK MAHASISWA MENGGUNAKAN ALGORITMA C4.5 (Studi Kasus Lulusan Fakultas Sains dan Matematika Universitas Diponegoro Tahun 2013/2014) Bramaditya Swarasmaradhana; Moch. Abdul Mukid; Agus Rusgiyono
Jurnal Gaussian Vol 3, No 4 (2014): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Based on academics regulation No. 209/PER/UN7/2012, the study period of students in Diponegoro University has been scheduled for 4 years. In this study the graduation status of students that graduate under or equal to 4 years categorized as graduate on time, meanwhile students that graduate over 4 years categorized as graduate out of time. Hence, it is important to understand the profile of students who graduate on time and out of time based on gender, majors, GPA, organizational experience, part time experience, scholarship, students origin and pathways scholar. The purpose of this study is to identify those students profiles using Algorithm C4.5. Algorithm C4.5 contructs a decision tree that able to handle missing values, able to handle continues attribute and able to simplify the trees by pruning. The accuration of the Algorithm C4.5 is 84.475% and the number of the nodes are 20 nodes where 13 nodes are leaf nodes. The students profile that identified graduate on time are students of Physics who had received scholarship and a woman; students of Chemistry with GPA > 3.06; students of Statistics with GPA > 3.43 from SNMPTN also PSSB and students of Mathematics with GPA > 2.96. Keywords: Study Period, Algorithm C4.5, Decision Tree.

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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

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Contact Name
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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