cover
Contact Name
-
Contact Email
-
Phone
-
Journal Mail Official
-
Editorial Address
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
Location
Kota semarang,
Jawa tengah
INDONESIA
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
PENCARIAN JALUR TERPENDEK MENGGUNAKAN METODE ALGORITMA “ANT COLONY OPTIMIZATION” PADA GUI MATLAB (Studi Kasus: PT Distriversa Buana Mas cabang Purwokerto) Via Risqiyanti; Hasbi Yasin; Rukun Santoso
Jurnal Gaussian Vol 8, No 2 (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 (1048.41 KB) | DOI: 10.14710/j.gauss.v8i2.26671

Abstract

For company, shortest distribution route is an important thing to be developed in order to obtain effectiveness in the distribution of products to consumers. One way of development is to find the shortest route with Ant Colony Optimization algorithm. This algorithm is inspired by the behavior of ant colonies that can find the shortest path from the nest to the food source. One example of a distribution company is PT Distriversa Buana Mas, also known as DBM. DBM is a physical distribution company covering the entire Indonesian archipelago specialized in the distribution of pharmaceuticals and consumer goods such as personal care, cosmetic and food products. DBM uses land transportation in 18 brances spread across Indonesia. One branch of DBM is in the Purwokerto region that distributes products to 29 stores in the Purbalingga region. This research is done with the help of GUI as a computation tool. Based on test results, the GUI system that has been built able to simplify and speed up the selection process of finding the shortest route for distribute product of DBM in the Purbalingga region. Keywords: Travelling Salesman Problem, Distriversa Buana Mas, Algorithm, Ant Colony Optimization, GUI
PENDEKATAN MODEL FUNGSI TRANSFER MULTI INPUT UNTUK ANALISIS HUBUNGAN ANTARA LUAS PANEN DAN LUAS TAMBAH TANAM DENGAN PRODUKSI BAWANG MERAH DI JAWA TENGAH Yunisa Ratna Resti; Abdul Hoyyi; Rita Rahmawati
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 (348.081 KB) | DOI: 10.14710/j.gauss.v4i3.9551

Abstract

Onion is one of holticulture commoditie which is consumed by many Indonesians with Central Java as its largest producer. The consumer’s need of onion keeps raising but, unfortunately, its number in the marketplace is limited. The onion supply depend on onion’s production which is affected by some factors, such as the land condition from the beginning when cultivation is started until the harvesting come such as area of harvesting and area of additional cultivation. So that onion’s production modeling which influenced by significant factores is needed to predict the crops volume in the future. Data which is used to production modeling are data of onion’s production in Jawa Tengah, these data is written by Dinas Pertanian Tanaman Pangan dan Hortikultura Jawa Tengah in everymonth. This research use multiple input transfer function model, which is an integration of ARIMA and regression model. This reseach aimed at modelling output series of onion production using two input series, i.e. area of harvesting and area of additional cultivation, from January 2004 to November 2014. The result showed that there is a significant correlation between area of harvesting and onion production, starting from lag t=0 during two periods, as well as area of additional cultivation toward the production from lag t=0. This multiple input transfer function method resulted in AIC valued at 3088.484. Keywords: Multiple Input Transfer Function, Onion
ANALISIS KETAHANAN HIDUP PENDERITA TUBERKULOSIS DENGAN MENGGUNAKAN METODE REGRESI COX KEGAGALAN PROPORSIONAL (Studi Kasus di Puskesmas Kecamatan Kembangan Jakarta Barat) Wulan Safitri; Triastuti Wuryandari; Suparti Suparti
Jurnal Gaussian Vol 5, No 4 (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 (881.966 KB) | DOI: 10.14710/j.gauss.v5i4.14735

Abstract

Tuberculosis (TB) is an infectious disease caused by the bacteria of the Mycobacterium groups that is Mycobacterium Tuberculosis. Most of the TB germs attack the lungs, but can also on other organs. In Indonesia based on the Survei Kesehatan Rumah Tangga (SKRT) in 2001 showed TB is the first cause of death in the group of infectious diseases. To determine the factors that affect the rate of healing of patients with TB is using regression analysis, because the dependent variable is the time of failure that equipped with censorship then used cox proportional hazard regression. Cox proportional hazard regression is a regression model that is often used in survival analysis. Survival analysis is the phrase used to describe the analysis of data in the form of times from a well-defined time origin until the occurrence of some particular event or end-point. The cases examined in this study are the factors that affect the rate of healing of patients with TB in Puskesmas Kecamatan Kembangan Jakarta Barat. The conclusion state that the factors affecting the rate of healing of patients with TB are a source of transmitting and medicine records. Keywords: Tuberculosis, Survival Analysis, Cox Proportional Hazard Regression
ANALISIS PREFERENSI MERK LAPTOP MAHASISWA UNIVERSITAS DIPONEGORO MENGGUNAKAN MODEL LOGIT TERSARANG Ain Hafidita; A Rusgiyono; Dwi Ispriyanti
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 (361.317 KB) | DOI: 10.14710/j.gauss.v3i4.7959

Abstract

Today’s rapidly evolving information technology affects mostly the change of people’s choice in electronic devices (gadget) usage, especially laptops. Addressing this phenomenon, laptop manufacturers are competing to create innovative products to reach various elements of the consumer. Nested logit, which sorts the alternatives based on common properties into smaller groups (nests) and has a level so as to form a tree structure, is a method that can be used to model consumer preferences. Alternatives may have either unique or common characteristics that describe properties or components so called attributes. In this study, laptop brands are treated as alternatives and classified by the operating system. This research concluded that the most favorite brand is Asus (25.35 %), followed by Toshiba (22.81%), Lenovo (14.27%), HP (13.90%), Acer (12.40%) and the least is Macbook (11.27%). Attributes that significantly affect the brand preferences are laptop classification and warranty, while color is considered insignificant.  
PERBANDINGAN NILAI KORELASI PADA KANONIK ROBUST (METODE MINIMUM COVARIANCE DETERMINANT) DAN KANONIK KLASIK (Studi Kasus Data Struktur Ekonomi dan Kesejahteraan Rakyat di Jawa Barat 2016) Widi Rahayu; Sudarno Sudarno; Alan Prahutama
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 (795.636 KB) | DOI: 10.14710/j.gauss.v8i4.26753

Abstract

Canonical correlation analysis is a multivariate statistical analysis that aims to examine the correlation between two groups of variabels in a way to maximize the value of correlation between variabels. The outlier in the data affect the covariance matrix is generated, So that use robust multivarat. There is robust multivariate approach to the analysis of canonical robust with MCD method (Minimum Covariance Determinant). This final project aims to determine comparison between correlation value of robust canonical with MCD and canonical classical methods. With a data theres containing of outliers in the case studies of people's welfare and economic structures in West Java in 2016. Used a set of variabels welfare of people consist of 6 variabel (Y) and a set of variabels economic structure which consists of four variabels (X). Based on the analysis results obtained that robust canonical correlation values better explain the correlation between two sets of variabels, the correlation value 0.99552, =0.91228, =0.71529, =0.63174, While the correlation value on classical canonical are 0.931489, 0.538672, 0.387099, 0.259318, Canonical robust can be interpreted more because it meets the test of significance are partially and directly, while the classical canon can not be interpreted further because it does not meet the test of the significance of the function. Keywords       : Classical canonical correlation, canonical correlation robust correlation value, Minimum Covariance Determinant (MCD)
ANALISIS KEPUTUSAN KONSUMEN MEMILIH BAHAN BAKAR MINYAK (BBM) MENGGUNAKAN MODEL REGRESI LOGISTIK BINER DAN MODEL LOG LINIER (Studi Kasus SPBU 44.502.10 Ketileng Semarang) Lintang Ratri Wardhani; Yuciana Wilandari; Triastuti Wuryandari
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 (363.172 KB) | DOI: 10.14710/j.gauss.v4i4.10228

Abstract

Fuel oil is a fuel derived and/or processed from petroleum. Fuel is often used for motor vehicles among others premium and pertamax. Some recent times has happened several times increase and decrease in fuel prices, even at the beginning of 2015 has happened  a new policy on the elimination of fuel subsidies. It affects on fuel consumption, especially consumption of premuim and pertamax. Many factors influence the consumer's decision in choosing a fuel, therefore needs to be analyzed to find out factors influencing consumer decision in choosing a fuel. This study was conducted to determine the factors that influence consumer decisions in choosing a fuel with a binary logistic regression model and the factors that influence the relationship with log linear models. Binary logistic regression is a method of data analysis used to find the relationship between the response variable (Y) that is binary or dichotomous with some predictor variables (X). Log linear models were used to analyze the relationship between categorical variables. Of a binary logistic regression model obtained influential variable is employment, vehicle age and income variable, with the biggest opportunity is 0,78862, is premium consumers with private employment, the age of the vehicle mote than 5 years and the income less than 1.500.000. for log linear models got the biggest opportunity is 0,91259, is premium consumers to the work of civil servant, the age of the vehicle mote than 5 years and the income less than 1.500.000. Keywords : fuel, binary logistic regression model, log linear models
PENERAPAN DIAGRAM KONTROL D^2 MAHALANOBIS PADA PROSES PRODUKSI MINUMAN KEMASAN RETURNABLE GLASS BOTTLE (Studi Kasus di PT. Coca-cola Bottling Indonesia Central Java) Muhammad Abid Muhyidin; Diah Safitri; Rita Rahmawati
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 | Full PDF (457.47 KB) | DOI: 10.14710/j.gauss.v3i3.6482

Abstract

Quality being one of the basic factors in choosing a product consumers. Therefore, an industry or a company should always maintain the quality of their products in order to get loyal customers and are able to survive in the competitive market. Coca-cola Bottling Indonesia Central Java Limited Compay is one of the manufacturing company engaged in the beverage packaging industry and  always trying to improve the quality for customer satisfaction. Although it has been to improve the quality, there are still defective product because it does not meet the quality characteristics. Monitoring the result of production process aims to determine whether the process is stable or not.  Mahalanobis control chartis  one of the control charts that can be used to monitor the production mismatch that is multivariate attributes. By using  Mahalanobis control chart, beverage production process of returnable glass bottle (RGB) in Coca-cola Bottling Indonesia Central Java Limited Compay based on the characteristics of disability shows that the results have not yet stable and controllable. This is  due to  Mahalanobis control chartphase II there are 5 observations of 75 observations or 6.66 % identified uncontrolled observations
ANALISIS INTEGRASI PASAR BAWANG MERAH MENGGUNAKAN METODE VECTOR ERROR CORRECTION MODEL (VECM) (Studi Kasus: Harga Bawang Merah di Provinsi Jawa Tengah) Rizky Aditya Akbar; Agus Rusgiyono; Tarno Tarno
Jurnal Gaussian Vol 5, No 4 (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 (576.718 KB) | DOI: 10.14710/j.gauss.v5i4.17110

Abstract

Spatial market integration is the degree of closeness of relationship between the regional market with other regional market. Vertical market integration is the level of the relationship between a marketing agency with other marketing agencies in the marketing. Spatial market integration in onion prices at the wholesale level for the area of Brebes, Tegal, Pemalang, Semarang, Salatiga, Surakarta and can be analyzed using the Vector Error Correction Model (VECM) to see where the long-term relationship. Vertical market integration in onion prices in the wholesale and consumer levels for Tegal, Semarang and Surakarta can be analyzed using the Granger Causality. The data used are the monthly time series data from January 2010 until February 2016, where data must be stationary at the first difference. Based on Johansen cointegration test obtained their long-term relationship at all six of the region and can be used to analyze VECM method. Granger Causality used as a test of causality. From this study, it can be concluded the onion market in Central Java is not fully integrated spatial whereby if shocks in Brebes then be transmitted to the market in Pemalang, Semarang, Salatiga and Surakarta whereas if shocks occur in Tegal will be transmitted to Semarang, Salatiga and Surakarta. This occurs because Brebes as the central region producing onion and Tegal as many areas in need of onion. The existence of vertical integration only occurs in Semarang, although only one-way causality. Keywords: Market Integration, Johansen Cointegration Test, VECM, Granger Causality Test.
KLASIFIKASI KELULUSAN MAHASISWA FAKULTAS SAINS DAN MATEMATIKA UNIVERSITAS DIPONEGORO MENGGUNAKAN MULTIVARIATE ADAPTIVE REGRESSION SPLINE (MARS) Rizal Yunianto Ghofar; Diah Safitri; Agus Rusgiyono
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 (563.274 KB) | DOI: 10.14710/j.gauss.v3i4.8095

Abstract

Education is a top priority for today's society. The quality of education can be seen from the learning achievement. There are so many factors that influence learning achievement in this regard graduation, therefore, necessary to identify the most influential factors that will be used to improve the quality of education. This study was conducted to obtain a model that is capable of classifying the data Faculty of Science and Mathematics Diponegoro University Semarang graduation using Multivariate Adaptive Regression Spline (MARS) method. MARS is a nonparametric regression method that can be used for data of high dimension. To get the best MARS models, made possible combinations Basis Function (BF), Maximum Interaction (MI), and Minimum Observation (MO) by trial and error. The best model is the model that is used in combination with BF = 28, MI = 2, MO = 1 because it has the smallest GCV value that is equal to 0,17781. There are three variables that contribute to the MARS model of the variable GPA, majors and gender. As for the variable organization, part time, entry point, and scholarships do not contribute to the model. Obtained misclassification of 20,50%. Press's Q test value indicates that statistically MARS method has been consistent in classifying the data FSM Diponegoro University Semarang graduation.
PENERAPAN SIX SIGMA DALAM RANCANGAN PERCOBAAN FAKTORIAL UNTUK MENENTUKAN SETTING MESIN PRODUKSI AIR MINERAL Muhammad Nugroho Karim Amrulllah; Mustafid Mustafid; 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 (697.572 KB) | DOI: 10.14710/j.gauss.v5i1.11037

Abstract

Machine setting is one of the factors which affects the high defects of mineral water cup. The determination of the optimal machine setting is needed to reduce the defects that occur. Six Sigma DMAIC (define, measure, analyze, improve, control) method in the factorial experimental design can be used for determining the optimal machine setting. This research, which is conducted in PT Sekar Sari, found the most optimal combination of pressure and temperature setting of the machine, so that the defects generated are decreasing after optimal condition treatment. Sigma level increased by 0.89 sigma, from 2,47 sigma to 3,36 sigma and COPQ (cost of poor quality) percentage decreased by 3.64%.Keywords: Six Sigma, DMAIC, Factorial Design of Experiment, COPQ.

Filter by Year

2012 2024


Filter By Issues
All Issue Vol 13, No 1 (2024): Jurnal Gaussian Vol 12, No 4 (2023): Jurnal Gaussian Vol 12, No 3 (2023): Jurnal Gaussian Vol 12, No 2 (2023): Jurnal Gaussian Vol 12, No 1 (2023): Jurnal Gaussian Vol 11, No 4 (2022): Jurnal Gaussian Vol 11, No 3 (2022): Jurnal Gaussian Vol 11, No 2 (2022): Jurnal Gaussian Vol 11, No 1 (2022): Jurnal Gaussian Vol 10, No 4 (2021): Jurnal Gaussian Vol 10, No 3 (2021): Jurnal Gaussian Vol 10, No 2 (2021): Jurnal Gaussian Vol 10, No 1 (2021): Jurnal Gaussian Vol 9, No 4 (2020): Jurnal Gaussian Vol 9, No 3 (2020): Jurnal Gaussian Vol 9, No 2 (2020): Jurnal Gaussian Vol 9, No 1 (2020): Jurnal Gaussian Vol 8, No 4 (2019): Jurnal Gaussian Vol 8, No 3 (2019): Jurnal Gaussian Vol 8, No 2 (2019): Jurnal Gaussian Vol 8, No 1 (2019): Jurnal Gaussian Vol 7, No 4 (2018): Jurnal Gaussian Vol 7, No 3 (2018): Jurnal Gaussian Vol 7, No 2 (2018): Jurnal Gaussian Vol 7, No 1 (2018): Jurnal Gaussian Vol 6, No 4 (2017): Jurnal Gaussian Vol 6, No 3 (2017): Jurnal Gaussian Vol 6, No 2 (2017): Jurnal Gaussian Vol 6, No 1 (2017): Jurnal Gaussian Vol 5, No 4 (2016): Jurnal Gaussian Vol 5, No 3 (2016): Jurnal Gaussian Vol 5, No 2 (2016): Jurnal Gaussian Vol 5, No 1 (2016): Jurnal Gaussian Vol 4, No 4 (2015): Jurnal Gaussian Vol 4, No 3 (2015): Jurnal Gaussian Vol 4, No 2 (2015): Jurnal Gaussian Vol 4, No 1 (2015): Jurnal Gaussian Vol 3, No 4 (2014): Jurnal Gaussian Vol 3, No 3 (2014): Jurnal Gaussian Vol 3, No 2 (2014): Jurnal Gaussian Vol 3, No 1 (2014): Jurnal Gaussian Vol 2, No 4 (2013): Jurnal Gaussian Vol 2, No 3 (2013): Jurnal Gaussian Vol 2, No 2 (2013): Jurnal Gaussian Vol 2, No 1 (2013): Jurnal Gaussian Vol 1, No 1 (2012): Jurnal Gaussian More Issue