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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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ANALISIS ANTREAN BUS NONPATAS AKAP DAN AKDP JALUR TIMUR TERMINAL TIRTONADI KOTA SURAKARTA Sitomurang, Rosalina Aprilda; Sugito, Sugito; Mukid, Moch. Abdul
Jurnal Gaussian Vol 7, No 3 (2018): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

The queuing system is a set of customers, services and a set of rules governing the arrival of its customers and services. Queue is a waiting phenomenon that is part of everyday human life. The queue is formed if the number of subscribers to be served exceeds the available service capacity. Queue phenomenon one of them seen in the queue nonpatas buses at Terminal Tirtonadi Surakarta. Nonpatas bus lanes studied include non-purpose buses Surabaya, Karanganyar, Wonogiri, Purwodadi and Pedesaan. The queue displant used is FIFO (First In First Out). For the five nonpatas bus lanes it meets steady state conditions because it has utility value less than 1. The selected model is a model that has the following 4 types of distributions: Erlang, Weibull, Gamma and Lognormal. The queue model generated for the five tracks (ERLA/ERLA/1):(GD/∞/∞) for Surabaya nonpatas buses, (ERLA/WEIB/1):(GD/∞/∞) for Karanganyar nonpatas buses, (GAMM/WEIB/1):(GD/∞/∞) for Wonogiri nonpatas buses, (ERLA/WEIB/1):(GD/∞/∞) for Purwodadi nonpatas buses, (WEIB/LOGN/1):(GD/∞/∞) for Pedesaan nonpatas buses. Based on the value of the system performance measure indicated that the five lines are queue system is good. Keywords: Beta, Erlang, FIFO, Gamma, Steady State Conditions, Lognormal, Queue Model, Queuing Systems, System Performance Measure, Weibull

ANALISIS INTERVENSI KENAIKAN HARGA BBM BERSUBSIDI PADA DATA INFLASI KOTA SEMARANG Novia Dian Ariyani; Triastuti Wuryandari; Yuciana Wilandari
Jurnal Gaussian Vol 4, No 3 (2015): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Intervention model is a model of time series data analysis that originally used to explore impact of unexpectedly external events to the observation variable. In this study, an increases subsidized fuel price analysis has done in June 2013 (first step function) and November 2014 (second step function) for Semarang inflation data at January 2007 until January 2015 and purposed to obtain the intervention model and forecast the Semarang inflation for some time later. Based on the result of inflated subsidized fuel price analysis for Semarang inflation data, the resulted model is ARIMA (1,0,0) with first intervention order b = 1, s = 2, r = 0 and second intervention order b = 1, s = 1, r = 0. Furthermore, the model is used to forecast inflation in Semarang for forward some periods.Keywords: ARIMA, intervention analysis, step function, inflation, subsidized fuel.

PENILAIAN CARA MENGAJAR MENGGUNAKAN RANCANGAN ACAK LENGKAP (Studi kasus: Cara Mengajar Dosen Jurusan Statistika UNDIP) Muhammad, Ilham; Rusgiyono, Agus; Mukid, Moch. Abdul
Jurnal Gaussian Vol 3, No 2 (2014): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Completely randomized design (CRD) is the simplest design among the designs of other experiments. In this treatment plan is fully charged randomized trial units or vice versa. Do research to find out how to rank professors teach statistics Diponegoro University Diponegoro University by alumnus statistics. This study used a RAL because only treatment variable that will be compared. Alumni variables as replication and assumed homogeneous. From the analysis of variance for the CRD, it is concluded that faculty groups differed significantly was A, P, O and L

REGRESI KOMPONEN UTAMA ROBUST S-ESTIMATOR UNTUK ANALISIS PENGARUH JUMLAH PENGANGGURAN DI JAWA TENGAH Jeffri Nelwin J. O. Siburian; Rita Rahmawati; Abdul Hoyyi
Jurnal Gaussian Vol 8, No 4 (2019): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Robust principal component regression s-estimator is principal component regression that applies robust approach method at principal component analysis and s-estimator at principal component regression analysis. The aim of robust principal component regression s-estimator is to overcome multicollinearity problems in multiple linier regression Ordinary Least Square (OLS) and to overcome outlier problems in principal component regression so get the most effective model. Minimum Volume Ellipsoid (MVE) is one of the robust approach methods that applied when doing principal component analysis and S-Estimator is one of the estimation methods that applied when doing principal component regression analysis. The case in this study is the factors that influence the Number of Unemployment in Central Java in 2017. The model that provides the most effective result to handling multicolliniearity and ouliers in the case study Number of Unemployment in Central Java in 2017 is using robust principal component regression MVE-(S-Estimator) with Adjusted R2 value of 0.9615 and RSE value of 0.4073. Keywords: Robust Principal Component Regression S-Estimator, Multicollinearity, Outliers, Minimum Volume Ellipsoid (MVE), Number of Unemployment.

KETEPATAN KLASIFIKASI KEIKUTSERTAAN KELUARGA BERENCANA MENGGUNAKAN REGRESI LOGISTIK BINER DAN REGRESI PROBIT BINER (Studi Kasus di Kabupaten Semarang Tahun 2014) Fajar Heru Setiawan; Rita Rahmawati; Suparti Suparti
Jurnal Gaussian Vol 4, No 4 (2015): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Population growth in Indonesia has increasedeach year. According to the population sensus conducted by National Statistics Bureau in 2010, Indonesia's population reached 237,6 million. Therefore, to control the population growth rate, government hold Keluarga Berencana (KB) or family planning program for couples in the childbearing age. The aim of this thesis which analyze the classification of couples in the childbearing age who follow family planning program, is to reduce the birth rate. So that, population can be controlled. The data used in this study is a Semarang Regency updated family data in 2014 that conducted Nasional Population and Family Panning Bureau. From the data, a binary logistic regression model and binary probit regression will be obtained, also classification accuracy will be obtained from each of these models. The analysis showed that the Binary Logistic Regression method produces a classification accuracy of 69,0% with 31,0% classification error. While, Probit Binary Regression method produces a classification accuracy of 68,4% with 31,6% misclassification. Binary Logistic Regression and Binary Logistic Regression method have a differences classification accuracy was very small then both are relative similar for analyze the classification family planning in Semarang Regency. Keywords: Keluarga Berencana (KB), Binary Logistic Regression, Binary Probit Regression, Classification,Confusion

ANALISIS ANTREAN BUS KOTA DI TERMINAL INDUK PURABAYA SURABAYA Priyambodo, Richy; Sugito, Sugito; Suparti, Suparti
Jurnal Gaussian Vol 1, No 1 (2012): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Transportation is an important factor to grow the economy of a region. This is because the more smoothly transport then the faster the economy growth of a region. For that, Purabaya bus station always try to provide optimum service to avoid long queue. Queue process is a process of the coming of a customer to a service facility, then waiting in line (queue) when the officers busy, and leaving the place after getting the service. If the queue at Purabaya bus station is pretty much, it will reduce the amount of revenue generated by the transport service provider. Therefore, we need a model of the queue to optimize service to customers in Purabaya bus station. From the analysis, the best queuing models obtained on the service system in Purabaya bus station is (M/G/c): (GD/∞/∞) to service system at the postal arrival with 5 counters, service system for each bus line in passenger service post is (M/G/1): (GD/∞/∞), and (G/G/2): (GD/∞/∞) to service system at the postal departure.

PERHITUNGAN VALUE AT RISK PADA PORTOFOLIO SAHAM MENGGUNAKAN COPULA (Studi Kasus : Saham- Saham Perusahaan di Indonesia Periode 13 Oktober 2011 - 12 Oktober 2016) Oktafiani Widya Ningrum; Tarno Tarno; Di Asih I Maruddani
Jurnal Gaussian Vol 6, No 2 (2017): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Investment is one of the way that is widely performed by people to achieve profitability in the future.Stock data is a data that is obtained from the observation that stock prices can be categorized into time series data, which usually have a tendency to fluctuate rapidly by the time so the variance of the residual will always change all the time or not constant, or often called heteroscedasticity case. Forecasting and data analysis is intended to minimize the risk and uncertainty factors. The risks can not be avoided but can be managed and estimated using Value at Risk (VaR) measurement tool. Copula theory is one of the tool that can be used to fit the joint distribution because it does not require the assumption of normality of the data so it is flexible enough for a variety of data, especially for financial data. This research is conducted using the method of Copula-GARCH to fit the three stocks of companies return data in Indonesia which have high volatility, those are PT Vale Indonesia Tbk (INCO), PT Bank Central Asia Tbk (BCA), and PT Indocement Tunggal Tbk (INTP) in period of October 13, 2011 to October 12, 2016 into ARIMA-GARCH model. The analysis is followed by copula on two stocks that have the highest ARIMA-GARCH residual correlation, those are BCA and INTP.Copula Gumbel is selected as the best copula with the amount of is 1,337. The risk derived from the calculation of Value at Risk (VaR) at the 99% confidence level is 3,922%, at the 95% confidence level is 2,397%, and at the 90% confidence level is 1,745%.Keywords : Value at Risk, Copula, GARCH

ANALISIS SISTEM ANTRIAN PELAYANAN TIKET KERETA API STASIUN TAWANG SEMARANG Yustiti, Merlia; Sugito, Sugito; Rusgiyono, Agus
Jurnal Gaussian Vol 3, No 4 (2014): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Semarang Tawang Station is one of the stations visited by customers. As it is known, the train journey is faster than the bus ride. Therefore, it is necessary to analyze queueing models that describe the condition to determine the size of the system performance and to see how the service provided by Customer Service, Ticket Reservation Counters/ Schedule Change/ Refund, Cancellation of the Ticket Counters, and Self Printing Ticket (CTM). Queueing model at the Customer Service and Self Printing Ticket (CTM) is (M/M/2):(GD/∞/∞), Ticket Reservation Counters/ Schedule Change/ Refund is (M/M/4):(GD/∞/∞), and Cancellation of the Ticket Counters is (M/G/1):(GD/∞/∞). Keywords : Arrival Distribution, Queueing Models, Size of the System Performance

IMPLEMENTASI METODE SIX SIGMA MENGGUNAKAN GRAFIK PENGENDALI EWMA SEBAGAI UPAYA MEMINIMALISASI CACAT PRODUK KAIN GREI Ayudya Tri Wahyuningtyas; Mustafid Mustafid; Alan Prahutama
Jurnal Gaussian Vol 5, No 1 (2016): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

The quality being a very important aspect for consumer to choose products beside price that competes. In production process grey fabric there are several kinds of defects, the defects can cause to decrease of grade fabric produced. Six sigma method is a method that can be used to analyze defect rate to approach zero defect products. A procedure used for quality improvement toward the target that the concept of six sigma DMAIC. This study aims to implement six sigma method and EWMA control chart in quality control of product quality cloth of grey. The results obtained in this study is one the whole production process produces DPMO value of 24790.97 with sigma quality level of 3.464 means that the product of one million cloth of grey there are 24790.97 meters of product that does not fit in production. In the calculation process capability, process capability ratio value obtained more than 1 means that the process is going well and meets the specifications that have been established, but it is still possible to be improved so that the products resulting better. Keywords: Quality, Quality Control, Six Sigma, EWMA

VALUASI COMPOUND OPTION PUT ON PUT TIPE EROPA Sutarno, Yulia Agnis; Maruddani, Di Asih I; Sugito, Sugito
Jurnal Gaussian Vol 3, No 3 (2014): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Options are one of the form of investment which a contract that gives the right (not obligation) to the option holder to buy (call options) or sell (put options) the underlying asset by a certain date for a certain price. Option price is a reflection of the intrinsic value of the option and any additional amount over intrinsic value. One type of options that are traded is compound options. Compound option model is introduced by Robert Geske in 1979. Compound options are options on options. Compound option put on a put is put option where the underlying assets are another put option. The compound option put on put will be exercised on the first exercise date only if the value of the put option on that date is less than the first stike price. An empirical study using compound option put on a put stocks of Apple Inc which is strike price compound option US$ 560, strike price put option US$ 585, with the first exercise date on March 28, 2014 and the second exercise date on May 17, 2014. The theoritical price of compound option put on put on stocks of Apple Inc is US$ 501.4566.

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