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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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Search results for , issue "Vol 4, No 1 (2015): Jurnal Gaussian" : 16 Documents clear

PEMODELAN TINGKAT PENGANGGURAN TERBUKA DI JAWA TENGAH MENGGUNAKAN REGRESI SPLINE Seta Satria Utama; Suparti Suparti; Rita Rahmawati
Jurnal Gaussian Vol 4, No 1 (2015): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Unemployment is one of the employment problems facing Indonesia. Central Java Province is one of the provinces with a high enough unemployment. The main indicators used to measure the unemployment rate in the labor force that is unemployed. Based on research Arianie (2012) labor force participation rate significantly affect the unemployment rate and based on research Sari (2012) the gross enrollment ratio significantly affects the rate of open unemployment. Therefore, in this study using the two predictor variables with the labor force participation rate as X1 and gross enrollment rate as X2. This study aimed to explore the model of open unemployment rate in the Province of Central Java. The method used is the method of spline regression. Spline regression has the ability to adapt more effectively to the data patterns up or down dramatically with the help of dots knots. Determination of the optimal point knots are very influential in determining the best spline models. The best spline models are models that have a minimum GCV (Generalized Cross Validation) Value. Best spline models for the analysis of the data rate of unemployment in Central Java Province is the spline regression model when order X1 is 2 and order X2 is 4 and large number of knots in the X1 is 1 knot at the point 68.02394 and X2 is 3 knots at the point 82.13, 87.19, and 87.65 with GCV value of 1.732746. Keywords: Rate of Open Unemployment, Spline Regression, GCV

ANALISIS INTERVENSI KENAIKAN HARGA BBM TERHADAP PERMINTAAN BBM BERSUBSIDI PADA SPBU SULTAN AGUNG SEMARANG JAWA TENGAH Fandi Ahmad; Rita Rahmawati; Diah Safitri
Jurnal Gaussian Vol 4, No 1 (2015): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Fuel consumption is always interesting to study, in addition to the use of which is used by all the community but also because of the critical role of fuel as an indicator to determine the price of other staples. Not surprisingly, changes in fuel prices polemical definitely interesting to study. In this subject specifically on the impact of the fuel price hike subsidized fuel demand. Changes in fuel price (hike) will have an impact on people's behavior in anticipation of the event. Most people will take the step to buy fuel in bulk prior to the date of determination of the increase in fuel prices, resulting in a surge in demand for fuel. Intervention model is a time series model that can be used to model and predict the data containing the intervention of external factors. In the intervention model, there are two functions, namely the step and pulse functions. Step function is a form of intervention that occurs within a long period of time while the pulse function is a form of intervention that occurs only within a certain time. Based on the analysis suggests that the impact of the use of gasoline and diesel at the pump Sultan Agung Semarang wear both pulse function because the impact was immediate and occur only in a short time Keywords: subsidized BBM, time series, intervention models, pulse function, step function

KAJIAN SIX SIGMA DALAM PENGENDALIAN KUALITAS PADA BAGIAN PENGECEKAN PRODUK DVD PLAYERS PT X Nailatis Shofia; Mustafid Mustafid; Sudarno Sudarno
Jurnal Gaussian Vol 4, No 1 (2015): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Increasingly rapid development period, many industry sectors are growing and developing in Indonesia. Quality basic consumer decision factor in selecting goods and services. In the process of checking the audio end section 8 types of defects found on the product DVD players. Damage that occurs due to several factors, including factors human, material factors, and factors machines. If the quality of a company is said to have good production systems with process control. Six Sigma method is a method that can be used for analysis of the defect rate to approach zero defect products. The procedures used for quality improvement towards the target that the concept of Six Sigma DMAIC. This study aims to apply Six Sigma methods in quality control by conducting case studies to improve product quality DVD player at the end of the audio process. The results obtained in this study is on the whole production process mengkasilkan DPMO value of 5487 with sigma quality level of 4.04 means that the product of one million DVD players there are 5487 units of product that does not fit in production. Keywords : Quality, Statistical Quality Control, Six Sigma

KLASIFIKASI LAMA STUDI MAHASISWA FSM UNIVERSITAS DIPONEGORO MENGGUNAKAN REGRESI LOGISTIK BINER DAN SUPPORT VECTOR MACHINE (SVM) Sri Maya Sari Damanik; Dwi Ispriyanti; Sugito Sugito
Jurnal Gaussian Vol 4, No 1 (2015): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Wisuda adalah hasil akhir dari proses kegiatan belajar mengajar selama mengikuti perkuliahan di perguruan tinggi. Dalam mencapai gelar S1 membutuhkan waktu normal yaitu selama empat tahun, tetapi ada banyak mahasiswa yang menyelesaikan studinya melebihi batas normal (lebih dari empat tahun) dan ada juga yang kurang dari empat tahun. Lama studi mahasiswa dapat dipengaruhi oleh banyak faktor antara lain Indeks Prestasi Kelulusan (IPK), jenis kelamin, jurusan, lama studi yang ditempuh, beasiswa, part time, organisasi, dan jalur masuk universitas. Pada penelitian ini, akan dilakukan klasifikasi berdasarkan status lama studi mahasiswa lebih dari empat tahun dan kurang dari sama dengan empat tahun. Metode yang digunakan untuk klasifikasi lama studi mahasiswa dengan jenis data nominal adalah Metode Support Vector Machine (SVM) dan akan dibandingkan dengan metode Regresi Logistik Biner. Berdasarkan hasil penelitian dengan metode regresi logistik biner, menunjukkan variabel yang berpengaruh terhadap lama studi mahasiswa adalah Jurusan dan IPK dengan ketepatan klasifikasi 70%. Sedangkan ketepatan klasifikasi dengan menggunakan SVM ketepatan klasifikasi tertinggi dengan menggunakan kernel linear, Polynomial dan RBF mencapai 90%.Kata kunci : Lama studi, Regresi Logistik Biner, Support Vector Machine (SVM), Ketepatan Klasifikasi.

PEMODELAN STATUS KESEJAHTERAAN DAERAH KABUPATEN ATAU KOTA DI JAWA TENGAH MENGGUNAKAN GEOGRAPHICALLY WEIGHTED LOGISTIC REGRESSION SEMIPARAMETRIC Firda Shintia Dewi; Hasbi Yasin; Sugito Sugito
Jurnal Gaussian Vol 4, No 1 (2015): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Welfare in society is one of the most important aspects in ensuring the realization of the social where people have a good level of welfare. Benchmarks achieved prosperity is the fulfillment of basic needs of society as feasible. Statistical methods have been developed for the analysis of spatial data by taking into account factors that Geographically Weighted Logistic Regression Semiparametric (GWLRS). GWLRS is a local form of the logistic regression where there are parameters that are influenced by the location (Geographically varying coefficient) and the parameters that are not influenced by the location (fixed coefficient). Selection of the optimum bandwidth using Cross Validation (CV). Model GWLRS Welfare Status district or city in Central Java showed that GWLRS models differ significantly from the logistic regression model. And models generated for each area will be different from each other. To get the best models, the number of models to be evaluated. One method for selecting the best model is the value of the Akaike Information Criterion (AIC). Based on AIC obtained the best model is the model GWLRS because it has the smallest AIC value of 46.11213 with a classification accuracy of 77.14%. Keywords: Welfare, Geographically Weighted Logistic Regression Semiparametric, Cross Validation, Akaike Information Criterion

ANALISIS KEPUASAN PENGUNJUNG MENGGUNAKAN SECOND ORDER CONFIRMATORY FACTOR ANALYSIS PADA STRUCTURAL EQUATION MODELING (Studi Kasus: Pengunjung Pemandian Air Panas (PAP) Guci) Niken Anggraini Dewi; Rita Rahmawati; Moch. Abdul Mukid
Jurnal Gaussian Vol 4, No 1 (2015): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Pemandian Air Panas (PAP) Guci is one of the famous natural destinations in Tegal regency. The visitors are fluctuated. Therefore, the writer carried out an analysis of visitor satisfaction using Stuctural Equation Modeling (SEM). Confirmatory factor analysis using in the reseach is second order. The construct used are the service quality (tangibles, reliability, responsiveness, insurance, and empathy), product quality (facilities, accessibility, source human and hygiene), price (affordability, suitability, and price comparisons), visitor satisfaction (overall satisfaction, satisfaction as expected, and the employee), and the interest reset. Choosing variables based on justification theory. Significant parameters, namely the quality service to the quality products by 50,8%, the quality product to the prices by 89%, the price to the visitor satisfaction of 91,4%, visitor satisfaction to the interest reset of 55%. Parameters were not significant, envelop service quality to price, quality service to visitor satisfaction, and quality product to visitor satisfaction. Keywords: Second Order Factor Analysis, SEM, Product Quality, Service Quality, Price, Visitor Satisfaction, Interest Reset.

PERBANDINGAN REGRESI KOMPONEN UTAMA DENGAN REGRESI RIDGE PADA ANALISIS FAKTOR-FAKTOR PENDAPATAN ASLI DAERAH (PAD) PROVINSI JAWA TENGAH Tazliqoh, Agustifa Zea; Rahmawati, Rita; Safitri, Diah
Jurnal Gaussian Vol 4, No 1 (2015): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Assuming violation multicollinearity in classical regression analysis can cause estimator resulting from classical model regression inefficient. Principal components regression and ridge regression are the methods that can be used to overcome the problem of multicollinearity. This research aimed to compare between the principal components regression with ridge regression to tackle the problem of multicollinearity in the analysis of the factors that affect revenue (PAD) of the Central Java province. The data used in this research are data revenue (PAD), and factors that affect the region, such as local tax, retribution, Gross Regional Domestic Products (GRDP) at current prices, Gross Regional Domestic Products (GRDP) at constant prices, population, regional spending. Based on the coefficient of determination value and test on individual regression coefficients, the value of variance inflation factor and correlations sufficiently high among some independent variables so we can conclude the existence of a violation of multicollinearity on analysis factors PAD. Based on standard error resulting from principal components regression and ridge regression show that principal components regression results in a standard smaller error. This shows that principal component regression is better than ridge regression in solving the problem multicollinearity on analysis of factors that affects pad province of central java. Keywords: Multicolinearity, revenue (PAD), Principal Component Regression, Ridge Regression, standard error

ANALISIS KORESPONDENSI UNTUK MENDAPATKAN PETA PERSEPSI DAN VARIABEL BAGI KEGIATAN USAHA (Studi Kasus Rumah Makan Spesial Sambal (SS) terhadap Pesaingnya) Susi Ekawati; Agus Rusgiyono; Triastuti Wuryandari
Jurnal Gaussian Vol 4, No 1 (2015): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Correspondence analysis is a technique for displaying the rows and columns of a data matrix primarily, a two-way contingency table as points in dual low-dimensional vector spaces. This technique is used to reduce the dimension of variables and describe the profile vector of rows and columns of the contingency table. This research aims to determine the position of the rivalry between the restaurants in Tembalang region based on consumer’s perceptions and to identify variables that distinguish it. The variables which used are including the price, taste, cleanliness, service, variety of food, and parking lots. Correspondence analysis is used to determine the variables that distinguish the 5th of the restaurant. The correspondence analysis produces a combined perceptual map with the satisfaction variables restaurant. From the analysis, it can be concluded that the perceptual map in the correspondence analysis shows the proximity between restaurant and satisfaction variables. Keywords : correspondence analysis, perceptual map, restaurant, satisfaction.

PENGELOMPOKAN PASIEN DEMAM BERDARAH RSUD dr. SOEHADI PRIJONEGORO DENGAN METODE ANALISIS KELAS LATEN Nurhayati, Noviana; Mukid, Moch. Abdul; Ispriyanti, Dwi
Jurnal Gaussian Vol 4, No 1 (2015): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

The degree of disease dengue patients in early at the hospital is latent or unknown directly. Therefore it needs an indicator variables such as the examination of hematocrit, leukocytes and platelets to classify patients with dengue fever into classes according to the degree of disease. In this study, the method used to classify patients with dengue fever is a latent class analysis method. The purpose of this study is to establish a latent class model and describes profile of the class on cases of grouping dengue fever patients in dr. Soehadi Prijonegoro Sragen. The results from latent class analysis showed that the latent class model formed is two latent class model. There are two classes formed is class 0 for disease dengue infection with danger signs have criteria a normal hematocrit, abnormal leukocyte and platelet abnormal and class 1 for disease dengue infection without signs of danger have criteria a normal hematocrit, normal leukocytes and normal platelets.Keyword : dengue fever, latent class analysis, latent variables

KETEPATAN KLASIFIKASI PEMILIHAN METODE KONTRASEPSI DI KOTA SEMARANG MENGGUNAKAN BOOSTSTRAP AGGREGATTING REGRESI LOGISTIK MULTINOMIAL Ahmad Reza Aditya; Suparti Suparti; Sudarno Sudarno
Jurnal Gaussian Vol 4, No 1 (2015): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Classification is one of the statistical methods in grouping the data compiled systematically. Classification problem rises when there are a number of measures that consists of one or several categories that can not be identified directly but must use a measure. classification methods commonly used in studies to analyze a problem or event is logistic regression analysis. However, this classification method provides unstable parameter estimation. So to obtain a stable parameter multinomial logistic regression model used bootstrap approach that is bootstrap aggregating (bagging). The purpose of this study was to compare the accuracy of the classification multinomial logistic regression models and bootstrap aggragatting model using the data of family planning in Semarang. From the results of bagging multinomial logistic regression obtained classification accuracy in replication bootstrap most 50 times at 51%, this model is able to decrease the classification error of up to 2% compared to the multinomial logistic regression model with a classification accuracy of 49%.Keywords: logistic regression, bootstrap aggregating, accuracy of classification

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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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Jawa tengah

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