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Jurnal Gaussian

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Published by Universitas Diponegoro

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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 733 Documents

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PREDIKSI RETURN PORTOFOLIO MENGGUNAKAN METODE KALMAN FILTER Dita Rosita Sari; Tatik Widiharih; Sugito Sugito
Jurnal Gaussian Vol 5, No 4 (2016): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Stock is an evidence for individual or institutional ownership about a company. To cover losses in stocks investment, should be done diversification to spread risk in some stocks called as portfolio. Portfolio is a joint of two or more stocks investment that are choosen as investment’s targets over spesific time periods and certain rules. To minimize losses in stocks investment, needed to predict portfolio return for some coming periods. Good prediction has small difference with actual data. One method that can minimize MSE is Kalman Filter. Kalman Filter estimates a process through feed back Control Mechanism called recursion. The variable used are monthly portfolio return of PT Mayora Indah Tbk and PT Indofood Sukses Makmur Tbk in January 2005 until December 2015. Data In January 2005 until December 2014 are used to predict the return portfolio for Year 2015. After that, an interval is made for those forecast results and compare with actual data. If actual data are residing in the interval, then Kalman Filter method can be used to predict portfolio return for year 2016. The MSE value with kalman Filter is 0,00225 and the MSE value with Box-Jenkis method is 0,00253, so Kalman Filter can minimize the MSE value. Keywords : portfolio return, Box-Jenkins, Kalman Filter

ANALISIS PAJAK KENDARAAN BERMOTOR MENGGUNAKAN MODEL MULTISCALE AUTOREGRESSIVE DENGAN MAXIMAL OVERLAP DISCRETE WAVELET TRANSFORM (Studi Kasus di UP3AD Kab.Temanggung) Wahyuningrum, Sri; Suparti, Suparti; Mukid, Moch. Abdul
Jurnal Gaussian Vol 3, No 1 (2014): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Time series analysis is applied in many fields, one of them is in the economic field. In this paper will consider analysis of the time series on data income taxes motor vehicles UP3AD Kab.Temanggung using Maximal Overlap Wavelet Transform Discrete (MODWT). Data time series decomposed using wavelet transform, namely MODWT with filter Haar and D4. From this transformation wavelet coefficients and scales coefficients are used for the modeling of time series. Modeling is done using the Multiscale Autoregressive (MAR) forecasting to get period ahead. Results of analysis showed that the model MAR with filter D4 is better than on the model MAR with filter Haar.

APLIKASI REGRESI DATA PANEL UNTUK PEMODELAN TINGKAT PENGANGGURAN TERBUKA KABUPATEN/KOTA DI PROVINSI JAWA TENGAH Tyas Ayu Prasanti; Triastuti Wuryandari; Agus Rusgiyono
Jurnal Gaussian Vol 4, No 3 (2015): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Open unemployment rate is the percentage of the labor force that is unemployed and actively seeking employment to the total labor force. Unemployment data is a combination of cross section data and time series data are commonly called panel data. This study aims to be modeling the open unemployment rate in Central Java province in 2008 to 2013 by using panel data regression. To estimate the panel data regression model, there are three approaches, the common effect model, fixed effect model and random effects model. Estimation of panel data regression model is used the fixed effect model with cross section weight. The model show that the percentage of population aged 15 years and over who worked by the highest education attained is Senior High School/Vocational School, Senior High School Gross Enrollment Rate (GER), dependency ratio and Gross Regional Domestic Product (GDP) significantly affect the open unemployment rate by generating for 81,65 %. Keywords: Cross Section Weight, Fixed Effect Model, Panel Data Regression, Open Unemployment, Central Java Province

PENGGUNAAN METODE PROJECTED UNIT CREDIT DAN ENTRY AGE NORMAL DALAM PEMBIAYAAN PENSIUN Ayu Hapsari Budi Utami; Yuciana Wilandari; Triastuti Wuryandari
Jurnal Gaussian Vol 1, No 1 (2012): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

One effort to anticipate the risk of old age is to include every worker in a pension plan. From that pension plan, workers will get a pension benefit at retirement. Before reaching retirement age, there should be an actuarial cost, which includes the normal cost and actuarial liabilities. Both are calculated using actuarial cost methods. Actuarial cost methods are divided into two major categories, are Accrued Benefit Cost Method and Projected Benefit Cost Method. One example of the methods included in Accrued Benefit Cost Method is Projected Unit Credit Method, and one of the methods included in Projected Benefit Cost Method is Entry Age Normal Method. The data used in this thesis are secondary data from PT Taspen (Persero) KCU Semarang. The results of the calculation shows normal cost using Projected Unit Credit method continues to increase with increased salary. Whereas if using Entry Age Normal Method the same amount for each year on an employee. Besides, actuarial liability using Projected Unit Credit Method is smaller than using Entry Age Normal for each employee in each year.

PEMODELAN RETURN SAHAM PERBANKAN MENGGUNAKAN EXPONENTIAL GENERALIZED AUTOREGRESSIVE CONDITIONAL HETEROSCEDASTICITY (EGARCH) Noveda Mulya Wibowo; Sugito Sugito; Agus Rusgiyono
Jurnal Gaussian Vol 6, No 1 (2017): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

ARIMA model is basically one of the models that can be applied in the time series data. In this ARIMA model, there is an assumption that the error variance of this model is constant. The price of stocks of the time series financial data, especially return has the trend to change quickly from time to time and it is actually fluctuative, so its error variance is inconstant or in another word, it calls as heteroscedasticity. To overcome this problem, it can be used the model of Autoregressive Conditional Heteroscedasticity (ARCH) or Generalized Autoregressive Conditional Heteroscedasticiy (GARCH). Furthermore, the financial data commonly has the different effect between the value of positive error and negative error toward the volatility data that is known as asymmetric effect. Indeed, one of the models used in this research, to overcome the problem of either heteroscedasticity or asymmetric effect toward the return of the close-stocks price of Banking daily is GARCH of asymmetric model that is Exponential Generalized Autoregressive Conditional Heteroscedasticity (EGARCH). The data of this research is the return data of the close-stocks price of Banking in November 1st 2013 to August 24th 2016. From the result of this analysis, it is gained several models of EGARCH. ARIMA model ([2,4],0,[2,4])-EGARCH (1,1) is such a best model for it has the lowest AIC value than any other models.Keywords: Return, Heteroscedasticity, Asymmetric effect, ARCH/GARCH, EGARCH.

METODE SERVQUAL-SIX SIGMA UNTUK PENINGKATAN KUALITAS PELAYANAN PUBLIK (Studi Kasus di Kantor Kecamatan Kedungbanteng, Purwokerto) Dian Andhika Prameswara; Mustafid Mustafid; Alan Prahutama
Jurnal Gaussian Vol 3, No 4 (2014): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Implementation public service is the fulfillment of civil rights that must be implemented by the government, so that its implementation must fit and be able to provide comfort and satisfaction for the society. Therefore, the performance of public services should be improved constantly and controlled so as to meet the needs of service users, because of the good and bad of a public service can be public benchmarks to assess the performance of the government. Measuring the quality of services is not as easy to measure the quality of the product, because the services are subjective. Therefore, the dimension of Servqual as a tool used to measure the performance of public services and Six Sigma to improve the performance of the public service. This study aims to apply the Servqual-Six Sigma methods with the aim to improve the performance of public services Kedungbanteng District Office. The results obtained in this study is that the dimensions of Servqual Six Sigma can be applied to improve the quality of public services.. As a whole, the results obtained indicate that the process of public service at the Kedungbanteng District Office not meet the standards of satisfaction targets 8. The process is based on the dimensions of Servqual is tangible, reliability, responsiveness, assurance, and empathy, respectively located in the sigma value 3,089; 3,102; 3,054; 3,195 and 3,219. This means, the number of mismatches that may arise from one million services performed for each dimension is respectively 5,61%; 5,46%; 6,01%; 4,5% and 4,28%. Keywords: Public service, Servqual, Six Sigma

IDENTIFIKASI VARIABEL YANG MEMPENGARUHI BESAR PINJAMAN DENGAN METODE POHON REGRESI (Studi Kasus di Unit Pengelola Kegiatan PNPM Mandiri) Shaumal Luqman; Moch. Abdul Mukid; Abdul Hoyyi
Jurnal Gaussian Vol 4, No 4 (2015): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Most people need a loan to fullfil their daily needs, such as a loan of goods or money. Loan can be obtained from financial institutions or individuals. In order to the loan granted by a financial institutions is not wrong target, financial institutions usually apply precaution principle. In making decisions related to how much a decent loan granted to a customer, the financial institutions often use the help of statistical methods. One methods often used is the Classification and Regression Trees (CART). Classification and Regression Trees (CART) is a nonparametric method that can be used to identify the variable that affect the amount of the loan at a financial institutions and estimate how much worth of loans granted. Because of the loan is a continous variable so the form of the tree is a Regression Tree. In this thesis, the financial institutions is UPK PNPM Mandiri Mekar Sejati in Kecamatan Bawang Kabupaten Batang. Variables that may be affected for large loans are age, occupation, type of warranty, the number family members, and the average income per month. The analysis showed that the variables that most influence on the income of the loans. Mean Absolute Percentage Error (MAPE) value from this method is 36%.Keyword : Regression tree, CART, Large loans.

PENENTUAN MODEL DAN UKURAN KINERJA PROSES ANTRIAN PADA UNIT PELAYANAN TEKNIK DINAS PUSKESMAS LIMBANGAN KABUPATEN KENDAL Fatkhan Arissetya; Sugito Sugito; Sudarno Sudarno
Jurnal Gaussian Vol 3, No 3 (2014): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

The UPTD (Unit Pelayanan Teknik Dinas) of Local Government Clinic of Limbangan in Kendal Regency is the only health-service in Limbangan Sub-district although there is another health-service such as doctors and midwifes. Since there are many people coming to the Local Clinic of Limbangan, it causes quite long queue. Therefore, it is needed to analyze the queuing model to finding out the system of the activity measure, so it can be concluded the queuing description and the service. If the distributrion of the arrival or the service is poisson or exponential, so the model is Markovial (M). However, if the distribution is not poisson or exponential, so the model is General (G). The queuing model of outpatients includes Regristrtion-Counter (M/G/1):(GD/∞/∞) , Medical Service (M/M/3):(GD/∞/∞) and Medicine-Counter (M/G/1):(GD/∞/∞). Meanwhile, the queuing model of hospitalized patients covers Hospitalized Rooms (M/M/16):(GD/∞/∞) and Payment Counter (M/G/1):(GD/∞/∞). It has been found out the best queue from the analysis in UPTD Local Government Clinic of Limbangan that is registration counter because the service time is quick and there are few queuing patients, so it won’t be hoarding

OPTIMASI VALUE AT RISK REKSA DANA MENGGUNAKAN METODE ROBUST EXPONENTIALLY WEIGHTED MOVING AVERAGE (ROBUST EWMA) DENGAN PROSEDUR VOLATILITY UPDATING HULL AND WHITE Khalida Hanum; Tarno Tarno; Sudarno Sudarno
Jurnal Gaussian Vol 6, No 3 (2017): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Risk measurement is important in making investments. One tool to measure risk is Value at Risk (VaR), which is the worst possible loss on a given time horizon under normal market conditions with a certain confidence level. The successful implementation of VaR depends on conditional volatility estimates of portfolio returns. Robust Exponentially Weighted Moving Average (robust EWMA) is one approach in forecasting the conditional volatility of asset returns. Robust EWMA is suitable for financial data analysis which is heteroscedastic and not normally distributed. The final VaR is calculated using historical simulation method with updated data return through volatility updating Hull and White procedure. In this research, robust EWMA is used for portfolio VaR calculation with case study of mutual funds shares BNI AM Dana Berkembang (BNI), Manulife Dana Saham Utama (MDSU) and Mega Asset Greater Infrastructure (MAGI). Validity testing of VaR was conducted based on Basel rule and Kupiec's proportion of failures (PF) test. The result of backtesting test shows that the obtained VaR are valid to predict the loss of the equity fund portfolio at both 95% and 99% confidence level.Keywords : mutual fund, Value at Risk, robust EWMA, volatility updating

ANALISIS JALUR TERHADAP FAKTOR-FAKTOR YANG MEMPENGARUHI INDEKS PRESTASI KUMULATIF (IPK) MAHASISWA STATISTIKA UNDIP Malik Hakam; Sudarno Sudarno; Abdul Hoyyi
Jurnal Gaussian Vol 4, No 1 (2015): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Education is a priority thing everyone today. Education is implemented in learning, by learning humans can develop all the potential there is in him. Learning is always related to the achievement of learning, because learning is a process while learning achievement is the result of the learning process. In the course of learning achievement levels measured by GPA (Grade Point Average). Factors that influence GPA among allowance, age, value of the UN Senior High School, many organizations, the internet long, long time to learn. Path analysis is the development of multiple regression which the independent variables affect the dependent variable not only directly but also indirectly affect. Based on the results of the discussion of the factors that affect the GPA is concluded that the allowance has indirect effect of -0,211, age has direct effect of age at 0,1901, the UN has direct effect of 0,258, many organizations have a direct effect of -0,3582 and has indirect effect of -0,132, the internet long direct effect of -0,2376 and has indirect effect of -0,038, long learning has a direct effect of 0,2344. Keywords: Education, GPA, Path analysis, Direct effect, Indirect effect

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