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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.
Arjuna Subject : -
Articles 733 Documents
PEMODELAN GENERALIZED SPACE TIME AUTOREGRESSIVE (GSTAR) SEASONAL PADA DATA JUMLAH WISATAWAN MANCANEGARA EMPAT KABUPATEN/KOTA DI JAWA TENGAH Ronny Gusnadi; Rita Rahmawati; Alan Prahutama
Jurnal Gaussian Vol 4, No 4 (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 (763.365 KB) | DOI: 10.14710/j.gauss.v4i4.10237

Abstract

In many applications, several time series data are recorded simultaneously at a number of locations. Time series data from nearby locations often to be related by spatial and time. This data is called spatial time series data. Generalized Space Time Autoregressive (GSTAR) model is one of space time models used to modeling and forecasting spatial time series data. This study applied GTSAR model  to modeling number of international tourist four locations in Magelang Regency, Surakarta City, Wonosobo Regency, and Karanganyar Regency. Based on the smallest RMSE mean of forecasting result, the best model chosen by this study is GSTAR(11)-I(1)12 with the inverse distance weighted. Based on GSTAR(11)-I(1)12 with the inverse distance weighted, the relationship between the location shown on International tourist arrivals Surakarta City influenced by the International tourist in other regencies. Keywords: GSTAR, RMSE, International Tourist
ANALISIS PEMBENTUKAN PORTOFOLIO OPTIMAL SAHAM DENGAN PENDEKATAN OPTIMISASI MULTIOBJEKTIF UNTUK PENGUKURAN VALUE AT RISK Fiki Farkhati; Abdul Hoyyi; Yuciana Wilandari
Jurnal Gaussian Vol 3, No 3 (2014): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/j.gauss.v3i3.6448

Abstract

Mean Variance Efficient Portfolio (MVEP) is theory of portfolio which purposed to standard investor  because approach has only one objective that minimize portfolio risk. Portfolio with multi-objective optimization that simultaneously maximize portfolio return and minimize portfolio risk with various weighting coefficient k represents risk aversion index. The purpose of this research is analyze proportion each stock in order that is formed optimal portfolio approach multi-objective optimization and analyze expected return and risk that suitable with preference investor. This research is based on cases stocks ASII, TLKM, SMGR, UNVR and LPKR. As a specific example investment Rp 50.000.000,00 in 20 days with 95% degree of confidence. Optimal portfolio for risk seeker investor is portfolio with     k = 0,01 with expected profit Rp 1.547.392,00 and risk estimation Rp 33.832.562,00. Optimal portfolio for risk indifference investor is portfolio with 1 ≤ k ≤ 100 with expected profit                Rp 965.678,00 until Rp 1.435.038,00 and risk estimation Rp 19.500.464,00 until                  Rp 25.513.351,00. Optimal portfolio for risk averse investor is portfolio with k = 10000 with expected return Rp 950.414,00 and risk estimation Rp 19.495.116,00. 
ANALISIS KETAHANAN HIDUP PENDERITA DENGUE HEMORRHAGIC FEVER (DEMAM BERDARAH) DENGAN REGRESI COX KEGAGALAN PROPORSIONAL SENSOR TIPE III Studi Kasus di Rumah Sakit Umum Daerah (RSUD) Temanggung Irfan Afifi; Di Asih I Maruddani; Abdul Hoyyi
Jurnal Gaussian Vol 6, No 3 (2017): 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 (595.233 KB) | DOI: 10.14710/j.gauss.v6i3.19309

Abstract

Dengue Fever is a disease caused by the dengue virus, transmitted from person to person through the bite of Aedes Aegypti and Aedes Albopictus mosquitoes. Dengue Fever mainly found in the tropical countries, such as Indonesia. According to World Health Organization (WHO) data, Indonesia reported as the 2nd country with the largest dengue cases among 30 endemic countries between 2004 until 2010.  Therefore, it is important to identify the factors influencing the recovery speed of dengue patients. This study utilize statitistical approach through regression analysis. One of the analysis methode choosen is survival analysis. This analysis is utilized to figure out the time series data analysis, of origin undefined time until the occurrence of certain events. In Survival Analysis, one of the regression method which is commonly used is  Cox regression. This study uses statistical methods approach through Cox regression proportional hazard to take into consideration the time of failure as the dependent variable. as well as the response variable function tends to a constant failure. object of research in this study are patients with dengue fever and the time the patient entered in a separate viewing the selected sensor type III This study used medical records of dengue fever patients of regional public hospital in Temanggung City, Central Java, from period of January to November 2016. Results obtained shows that the factors affecting the recovery speed of patients is Hematocrit state of the patient. Patients with normal Hematocrit state have faster recovery that patients with upnormal circumtances.  Keywords: Dengue, Survival Analysis, Regression Cox Proportional Hazard
PEMETAAN PREFERENSI MAHASISWA BARU DALAM MEMILIH JURUSAN MENGGUNAKAN ARTIFICIAL NEURAL NETWORK (ANN) DENGAN ALGORITMA SELF ORGANIZING MAPS (SOM) Muh Najib Hilmi; Yuciana Wilandari; Hasbi Yasin
Jurnal Gaussian Vol 4, No 1 (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 (569.764 KB) | DOI: 10.14710/j.gauss.v4i1.8145

Abstract

College is the highest educational institution and the role the intellectual life of the Indonesian people that the main purpose of academics. Not all colleges into their destination but only college that has a role, credibility and rank the best course of which it is their goal. This makes higher education marketing research approach to get attention and become the main goal of the academics in choosing a college. This research was conducted in order to determine with certainty attribute / emotional reasons academics in choosing college as their academic goals. The method used in this study were self-organizing maps with the Kohonen algorithm is a classification method. Kohonen SOM algorithm with learning rate used 0:05, 0.25, 0:50, 0.75, 0.95 and initialization of initial weight value and the value of the midpoint and 500 iterations with output 3 clusters are formed. Results clustering of SOM validated using Davies-Bouldin index with the best clustering results that DBI minimum (1.7802) with the learning rate is 0.95 and the cluster formed three clusters for the first cluster as many as six members, cluster-2 by 9 members and 3rd cluster as 5 members the results of clustering with top priority contained in the cluster to-2 with a mean (7.434) with the characteristics of each member is an emotional reason in choosing a major. Keywords: Self Organizing Maps, Kohonen algorithm, Learning Rate, Index Davies Bouldin, Cluster.
Ketepatan Klasifikasi Status Pemberian Air Susu Ibu (ASI) Menggunakan Multivariate Adaptive Regression Splines (MARS) dan Algoritma C4.5 di Kabupaten Sragen Yusuf Arifka Rahman; Suparti Suparti; Sugito Sugito
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 (502.401 KB) | DOI: 10.14710/j.gauss.v5i1.11062

Abstract

The progress of a nation influenced and determined by the level of public health, the indicator of the level of health is determined by nutritional status. Nutrition can be given early, namely breastfeeding to infants. This research aims to compare the classification of exclusive breastfeeding and nonexclusive breastfeeding. It used two methods for classifying a breastfeeding to babies in Sragen subdistrict on 2014, the methods are Multivariate Adaptive Regression Splines (MARS) and C4.5 Algorithm. MARS is nonparametric regression method that use to overcome the high dimension of data that produces accurate prediction and continuous models on knot. C4.5 Algorithm is a way of classifying methods from data mining that use to construct a decision tree. To evaluate the result of classification use Apparent Error Rate (APER) calculation. The best classification  result using MARS method is by using the combination of Basis Function (BF)=40, Maximum Interaction (MI)=3, Minimum Obsevation (MO)=3 because it will result on the smallest Generalized Cross Validation (GCV). Classification result using MARS method obtained APER is 19,7674% and 80,2326% of accuracy. Classification result using C4.5 Algorithm obtained APER is 18,6047% and 81,3953% of accuracy. From proportion test, concluded classification that formed by MARS is as good as by C4.5 Algorithm. Keywords: Breastfeeding, Classification, MARS, C4.5 Algorithm
PEMETAAN PERSEPSI MERK LAPTOP DI KALANGAN MAHASISWA MENGGUNAKAN ANALISIS KORESPONDENSI BERGANDA (Studi kasus: Mahasiswa Universitas Diponegoro Semarang) Anissa Pangastuti; Moch. Abdul Mukid; Sudarno Sudarno
Jurnal Gaussian Vol 2, No 3 (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 (381.237 KB) | DOI: 10.14710/j.gauss.v2i3.3662

Abstract

The growth of technology makes producer compete creating sophisticated, modern, and practical tools. One of them is competing creating notebook. Some brands that more develop than other brands in the market are Toshiba, Acer, Asus, HP and Dell. This research studies about positioning one brand against other brands in the market and proximity between all brands that affected by some factors. There are, processors, designation notebook for consumer, features, endorsement and guarantee, endurance notebook against damage, and the distant age of notebook consumption when it has damage in hardware for the first time. Because there are so many factors that affecting perceptual mapping and positioning notebook at the market, hence it need to be analyzed using multiple correspondence analysis. Multiple correspondence analysis is an expansion technique from simple correspondence analysis which is a multivariate technique graphically used for exploration data from a multi-way contingency table. The result of this research makes conclusion that there is a similarity between Acer and HP notebook. This statement be marked with proximity of point Acer and HP. It can be seen from the incision magnitude between both of that brands. There are both of them be used for graphic and designing, have the same complete features and for time of damage for the first time that both of that brands experienced are at age > 3 years
KAJIAN RELIABILITAS PADA SISTEM SERI-PARALEL DENGAN EMPAT KOMPONEN Farhah Izzatul Jannah; Sudarno Sudarno; Alan Prahutama
Jurnal Gaussian Vol 7, No 1 (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 (586.835 KB) | DOI: 10.14710/j.gauss.v7i1.26637

Abstract

Reliability analysis is the analysis of the possibility that the product or service will function properly for a certain period of time under operating conditions without failure. One configuration of components that can be formed is a series-parallel system on a filter capacitor circuit using 4 components consisting of 2 rectifier diodes, 1 capacitor, and 1 load resistor. The data used to obtain the value of system reliability is the time of failure based on the assumption of failure of the independent component. The function of the form on the system can be expressed by Ф(x)= x1x3 + x1x4 + x2x3 + x2x4 - x1x3x4 - x2x3x4 - x1x2x3 - x1x2x4 + x1x2x3x4. The parameter values of each distribution are calculated using the Median Rank Regression Estimation (MRRE) and Maximum Likelihood Estimation (MLE) methods. To test the data following a certain distribution or not, the calculation is manually done with the Anderson-Darling (AD) test so that it is known that the failure time data of rectifier diode 1 follows the weibull distribution with parameters  and , failure time data of rectifier diode 2 follows weibull distribution with parameters  and , failure time data of capacitors follow normal distribution with parameters  and , and the failure time data of the load resistor following the gamma distribution with parameters  and . From the calculation of system reliability, it shows that the higher the intensity of the system fails it will affect the value of reliability to be lower. A serial system from a parallel system functions if there is at least one component j in one subsystem that functions. Keywords: Reliability, Series-Parallel, MRRE, MLE, AD.
ANALISIS SISTEM PELAYANAN DI STASIUN TAWANG SEMARANG DENGAN METODE ANTRIAN Nursihan Nursihan; Sugito Sugito; Hasbi Yasin
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 (312.433 KB) | DOI: 10.14710/j.gauss.v4i2.8586

Abstract

Semarang Tawang Station is one of the stations visited by customers. As it is known that the train journey into one of the fastest alternative but to use other means of transportation. Therefore, it is necessary to analyze queuing model that describes the conditions to determine the size of the performance of the system to see how the service provided. When the distribution is a Poisson arrival or services or the exponential model (M) but if the distribution is not Poisson or exponential, the model General (G). Model queue at the station with the number of arrivals and the number of services is (M/M/5):(GD/∞/∞). Keywords: Processqueue, Semarang Tawang station, queuing models.
PENGARUH MARKETING MIX TERHADAP KEPUASAN DAN LOYALITAS KONSUMEN MENGGUNAKAN METODE STRUCTURAL EQUATION MODELLING (SEM) Syarah Widyaningtyas; Triastuti Wuryandari; Moch. Abdul Mukid
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 (737.852 KB) | DOI: 10.14710/j.gauss.v5i3.14712

Abstract

Marketing mix is a combination of variables that constitute the core of marketing system, consisting a set of variables that can be controlled and used by companies to influence consumer responses in target markets comprise. One that used in this study for analysis is Structural Equation Model (SEM). The study shows that satisfaction influenced by promotion, pricing, product and location of 38,9%, that loyalty is explained by satisfaction, promotion, pricing, product and location of 99,8%. In significant testing, it was found that pricing, product, location are significant to satisfaction. Satisfaction is significant to loyalty; while pricing, location, product are not significant to loyalty. Promotion is not significant to satisfaction and loyalty. Based on the results of data processing using software AMOS 22.0, the model SEM has been convenient and fit for use in research because the data has been proven to have normal distribution and have met the criteria for Goodness of Fit.Keywords: Marketing Mix, Consumer Satisfaction, Consumer Loyalty, Structural Equational Modelling.
PEMODELAN LAJU KESEMBUHAN PASIEN RAWAT INAP TYPHUS ABDOMINALIS (DEMAM TIFOID) MENGGUNAKAN MODEL REGRESI KEGAGALAN PROPORSIONAL DARI COX (Studi Kasus di RSUD Kota Semarang) Bellina Ayu Rinni; Triastuti Wuryandari; Agus Rusgiyono
Jurnal Gaussian Vol 3, No 1 (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 (594.229 KB) | DOI: 10.14710/j.gauss.v3i1.4773

Abstract

Typhus Abdominalis (typhoid fever) is a systemic infectious disease caused by Salmonella typhi and ranked 3rd of 10 major inpatient diseases in the hospitals of Indonesia based on Indonesia’s health profile data in 2010. It's important to know the factors that can affect the rate of recovery of hospitalized patients suffering from typhoid fever. One way is to use survival analysis that is a statistical method to analyze survival data. Cox proportional hazards regression is a model in survival analysis used to determine the relationship between one or more independent variables and the dependent variable. This model does not require information about the underlying distribution, but the hazard functions of different individuals assumed to be proportional. The Data used are from 45 patients of thypoid fever on RSUD Kota Semarang who have been medically recorded from  August 1st 2012 until November 30st 2012. Furthermore it is concluded that the factors that affect the rate of recovery of inpatients suffering from typhoid fever were age.

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