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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
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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.
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Articles 733 Documents
APLIKASI METODE MOMEN PROBABILITAS TERBOBOTI UNTUK ESTIMASI PARAMETER DISTRIBUSI PARETO TERAMPAT PADA DATA CURAH HUJAN (Studi Kasus : Data Curah Hujan di Kota Semarang Tahun 2004-2013) Rengganis Purwakinanti; Agus Rusgiyono; Alan Prahutama
Jurnal Gaussian Vol 3, No 4 (2014): 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 (637.586 KB) | DOI: 10.14710/j.gauss.v3i4.8093

Abstract

The method used to analyze the extreme rainfall is Extreme Value Theory (EVT). One of the approaches in the EVT is Peak Over Threshold (POT) which follows the Generalized Pareto Distribution (GPD). The shape and scale parameter estimates obtained using the method of probability weighted moment. The results of this research were presumptive maximum value within a period of 1 year to the period 2004 to 2013 showed that year 2009/2010 has the possibility of extreme value compared with other years. Also obtained Mean Absolute Percentage Error values ( MAPE ) of 33.19 %. This result is a big difference because the MAPE values above 10 %, thus allowing the emergence of extreme values. Keywords: Rainfall, Extreme Value Theory, Peak Over Threshold, Generalized Pareto Distribution, Probability Weighted Moment
PEMODELAN UPAH MINIMUM KABUPATEN/KOTA DI JAWA TENGAH BERDASARKAN FAKTOR-FAKTOR YANG MEMPENGARUHINYA MENGGUNAKAN REGRESI RIDGE Hildawati Hildawati; Agus Rusgiyono; Sudarno Sudarno
Jurnal Gaussian Vol 5, No 1 (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 (543.998 KB) | DOI: 10.14710/j.gauss.v5i1.11035

Abstract

The least squares method is a regression parameter estimation method for simple linear regression and multiple linear regression. This method produces no bias and variance estimator minimum if no multicollinearity. But if it happens, it will generate a large variance and covariance. One way to overcome this problem is by using ridge regression. Ridge regression is a modification of the least squares by adding a bias constant  on the main diagonal Z'Z. So that estimation parameter  with . This method produces bias and variance estimator minimum. Results of the modeling discussion of minimum wage in the city of Semarang, Surakarta, Tegal and Banyumas as well as the factors that influence it, such as inflation, Gross Domestic Regional Product (DGRP) and the Desent Living Needs contained multicollinearity problem. The minimum wage is significantly influenced Semarang Desent Living Needs, while Surakarta and Banyumas significantly affected GDRP and Desent Living Needs. Keywords: multicollinearity, ridge regression, bias constants , the minimum wage
ANALISIS SPASIAL PENYEBARAN PENYAKIT DEMAM BERDARAH DENGUE DENGAN INDEKS MORAN DAN GEARY’S C (STUDI KASUS DI KOTA SEMARANG TAHUN 2011) Nuril Faiz; Rita Rahmawati; Diah Safitri
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 (682.645 KB) | DOI: 10.14710/j.gauss.v2i1.2745

Abstract

Dengue Haemorrhagic Fever (DHF) is an infectious disease transmitted by the mosquito Aedes aegypti through its the virus dengue virus from patient to another via the bite. Rate dependence dengue in an area estimated to be affected by dengue fever in other neighboring areas. The statement was supported by the First Law of Geography expressed Tobler that all things related to everything else, but near things are more related than distant things. Therefore, if a dengue endemic area, the suspected region make the area immediately adjacent to endemic dengue with a new one. The purpose of this study was to determine whether there is spatial autocorrelation in the spread of dengue fever in the city of Semarang. Limited to methods index and Geary's C Moran and mapping the spread of dengue fever in the city of Semarang with respect to the location (district) in 2011. Of the two methods used showed a pattern of spread of Dengue Hemorrhagic Fever (DHF) are spatially in Semarang and show positive spatial autocorrelation, indicating a nearby location to have similar values, and tend to cluster. Keyword: Dengue Hemorrhagic Fever (DHF), Spatial, Moran Index, Geary’s c.
MODEL FEED FORWARD NEURAL NETWORK (FFNN) DENGAN ALGORITMA PARTICLE SWARM SEBAGAI OPTIMASI BOBOT (Studi Kasus : Harga Daging Sapi dari Bank Dunia Periode Januari 2007 – Desember 2018) Faisal Fikri Utama; Budi Warsito; Sugito Sugito
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 (443.97 KB) | DOI: 10.14710/j.gauss.v8i1.26626

Abstract

Beef is one of the important food commodities to fulfill the nutritional adequacy of humans. The World Bank notes the beef prices that are exported worldwide every month. For this reason, those data becomes a predictable series for the next period. Feed Forward Neural Network is a non-parametric method that can be used to make predictions from time series data without having to be bound by classical assumptions. The initiated weight will be evaluated by an algorithm that can minimize errors. Particle Swarm Optimization (PSO) is an optimization algorithm based on particle speed to reach the destination. The FFNN model will be combined with PSO to get predictive results that are close to the target. The best architecture on FFNN is obtained with 2 units of input, 1 unit of bias, 3 hidden units, and 1 unit of output by producing MAPE training 11.7735% and MAPE testing 8.14%. According to Lewis (1982) in Moreno et. al (2013), the MAPE value below 10% is highly accurate forecasting. Keywords: Feed Forward Neural Network (FFNN), Particle Swarm Optimization (PSO), neurons, weights, predictions.
PEMILIHAN PENGRAJIN TERBAIK MENGGUNAKAN MULTI-ATTRIBUTE DECISION MAKING (MADM) TECHNIQUE FOR ORDER PREFERENCE BY SIMILARITY TO IDEAL SOLUTION (TOPSIS) (STUDI KASUS : PT. Sinjaraga Santika Sport, Majalengka) Fizry Listiyani Maulida; Tatik Widiharih; 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 (721.974 KB) | DOI: 10.14710/j.gauss.v4i2.8574

Abstract

The human resources (HR)  known as the employess are the successful of the company. PT. Sinjaraga Santika Sport (Triple’S) is a handmade football company by the craftsmen. Most of the craftsmen go to the rice fields on the growing season or the harvest season. So selection of the best craftsmen is needed in order to the production of the football don’t have problems. The selection uses TOPSIS method. TOPSIS is one of method that can be used to solve MADM problem. The steps of TOPSIS method are calculated the normalized decision matrix, determined the weight, calculated the weighted normalized decision matrix, determined the positif-ideal solutions and negatif-ideal solutions, calculated the separation measures, and calculated the preference value. There are 25 craftsmen and six criteria. The criteria are neatness of the ball, accurateness stitching of the ball, number of the ball, accurateness logo of the ball, cleanness of the ball, and defect proportion. The results in this reseach are the best carftsmen has 0,78861 of preference value and the worst craftsmen has 0,16642 of preference value. Preference value by manual calculate equal with preference value by GUI Matlab. Keywords : TOPSIS, MADM, carftsmen
MODEL REGRESI COX STRATIFIED PADA DATA KETAHANAN Mohamad Reza Pahlevi; Mustafid Mustafid; Triastuti Wuryandari
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 (559.772 KB) | DOI: 10.14710/j.gauss.v5i3.14701

Abstract

Stratified Cox model on the events are not identical is a modification of the Cox Proportional Hazard models when there are individuals who experienced more than one incident. This study aims to form a stratified Cox regression models for repeated occurrences of data are not identical and their application to cases of hemorrhagic stroke disease recurrence and to determine the factors that affect the case. Parameter Estimation in Stratified Cox models using Partial Maximum Likelihood Estimation (MPLE). Stratified Cox model building procedure consists of six stages: (1) identification data, which specify the variables that will be used in the Cox models. (2) Estimated Cox Proportional Hazard model parameters. (3) The test parameters for each variable using the Wald test. (4) Testing Proportional Hazard assumptions. (5) stratification variables. (6) Interpretation Stratified Cox models. This study uses data of patients who experienced a hemorrhagic stroke unspecified with 7 independent variables such as age, sex, blood pressure, blood sugar, triglycerides, cholesterol and replications. Based on the testing parameters obtained three variables that influence such as age, cholesterol levels and repeat. Furthermore, in assuming Proportional Hazard showed that replicates variable Proportional Hazard did not meet the assumptions that need to be stratified. Unspecified hemorrhagic stroke patients aged over 50 years admitted to 3.230 times longer than the patients were under 50 years old. Unspecified hemorrhagic stroke patients with high cholesterol levels are treated 0.182 times faster than patients with normal cholesterol levels. Keywords: Stratified Cox, Cox Proportional Hazard, MPLE, Haemorrhagic Stroke, Recurrent Events
APLIKASI MODEL REGRESI SPASIAL UNTUK PEMODELAN ANGKA PARTISIPASI MURNI JENJANG PENDIDIKAN SMA SEDERAJAT DI PROVINSI JAWA TENGAH Restu Dewi Kusumo Astuti; Hasbi Yasin; Sugito Sugito
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 (630.521 KB) | DOI: 10.14710/j.gauss.v2i4.3804

Abstract

Net Enrollment Ratio (NER) is an  instrument to measure education rate. But NER rate of Senior High School in Central Java Province is only 47,34 %. This study discuss about regression model of factors which influence NER of Senior High School for Central Java province considering  spatial effects for each regency  in Central Java province. The examination of spatial effects shows that there is spatial dependence in response variable so this study is developed by using Spatial Autoregressive Model (SAR). The methods for estimating the parameter are   Ordinary Least Square and Maximum Likelihood Estimation. The result of this study shows that the average number of household members has significant spatial effect for NER rate of Senior High School in Central Java Province. From the comparison AIC value, it was found that SAR model is better to analyze NER rate of Senior High School in Central Java province than classic one.
KETAHANAN HIDUP PASIEN GAGAL GINJAL DENGAN METODE KAPLAN MEIER (Studi Kasus di Rumah Sakit Umum Daerah dr. R. Soedjati Soemodiarjo Purwodadi) Immawati Ainun Habibah; Tatik Widiharih; Suparti Suparti
Jurnal Gaussian Vol 7, No 3 (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 (301.083 KB) | DOI: 10.14710/j.gauss.v7i3.26660

Abstract

Chronic Kidney Disease (CKD) is a failure of kidney function that which get slowly and can not recover. Most of the patients CKD get death sudden becuse of cardiovascular complications (related to the heart and blood vessels) however only minor part can reach terminal phase (CKD stage 5) which need replacement therapy of Kidney. Replacement therapy of Kidney are hemodialysis, peritoneal dialysis, and Kidney transplant. Because of that, the importance to study how long the patient opportunity is life endurance analysis.  Survival analysis methods to life depend from the life time and status of individual life time. Survival analysis uses Kaplan-Meier method. During the observation process, there is different observations so censor type III is choosen. Censor type III is censoring type which research is done to individual in and out for determine time, because of that estimation value of survival can be caunted using Kaplan Meier method with censor type III. This research uses medical records data from the patients with kidney failure period 1 January 2014 until 30 November 2017 in RSUD dr.R. Soedjati Soemodiarjo Purwodadi Grobogan Regency. The results of the analysis and discussion are known that if hemodialysis getting longer done, estimation value of survival. With an average estimate of survival is 776 days. Keywords: Chronic Kidney Disease, Survival Analysis, Kaplan Meier
PENERAPAN DIAGRAM KONTROL T2 HOTELLING PADA PROSES PRODUKSI KACA Muhammad Hilman Rizki Abdullah; Rita Rahmawati; 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 (561.466 KB) | DOI: 10.14710/j.gauss.v4i3.9482

Abstract

SPC (Statistical Process Control) is a method used to monitoring the process of identifying the causes of variance and improve processes. In term of its variable characteristic, quality control in SPC can be divided into two kinds of univariate control charts and multivariate control charts. T2 Hotelling control chart is a multivariate control charts used in quality control process mean. In the process of glass production, This research was conducted in two stages by making use three major characteristics of quality, those are thickness, length and width. Application of T2 Hotelling control chart on the first phase of the signal are out of control, so it is necessary to identify the variable signal causes the uncontrolled use Decomposition MYT (Mason, Young and Tracy). Based on the identification of variables obtained that the variable width is the cause of the signal out of control. In the second phase is stable glass production process it shows the company has made improvements to the production process of phase II. Keywords: Statistical Process Control, Quality Control, Hotelling T2 control  chart, signal  out of control
KLASIFIKASI CALON DEBITUR KREDIT PEMILIKAN RUMAH (KPR) MULTIGUNA TAKE OVER MENGGUNAKAN METODE k NEAREST NEIGHBOR DENGAN PEMBOBOTAN GLOBAL GINI DIVERSITY INDEX Inas Hasimah; Moch. Abdul Mukid; Hasbi Yasin
Jurnal Gaussian Vol 8, No 4 (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 (504.102 KB) | DOI: 10.14710/j.gauss.v8i4.26721

Abstract

House credit (KPR) is a credit facilities for buying or other comsumptive needs with house warranty. The warranty for KPR is the house that will be purchased. The warranty for KPR multiguna take over is the house that will be owned by debtor, and then debtor is taking over KPR to another financial institution. For fulfilled the credit to prospective debtor is done by passing through the process of credit application and credit analysis. With the credit analysis, will acknowledge the ability of debtor for repay a credit. Final decision of credit application is classified into approved and refused. k Nearest Neighbor by attributes weighting using Global Gini Diversity Index is a statistical method that can be used to classify the credit decision of prospective debtor. This research use 2443 data of KPR multiguna take over’s prospective debtor in 2018 with credit decision of prospective debtor as dependent variable and four selected independent variable such as home ownership status, job, loans amount, and income.  The best classification result of k-NN by Global Gini Diversity Index weighting is when using 80% training data set and 20% testing data set with k=7 obtained  APER value 0,0798 and accuracy 92,02%. Keywords: KPR Multiguna Take Over, Classification, KNN by Global Gini Diversity Index weighting, Evaluation of Classification

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