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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.
Arjuna Subject : -
Articles 733 Documents
FAKTOR-FAKTOR YANG MEMPENGARUHI STATUS KELULUSAN BERDASARKAN JALUR MASUK MAHASISWA DENGAN MODEL REGRESI LOGISTIK BINER BIVARIAT (Studi Kasus Mahasiswa FSM Universitas Diponegoro) Safitri Daruyani; Yuciana Wilandari; Hasbi Yasin
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 (444.793 KB) | DOI: 10.14710/j.gauss.v2i4.3805

Abstract

The acceptance of college students in public universities are divided into two ways, the National Selection of Public University Entrance by invitation and the National Selection of Public University Entrance by non invitation. The National Selection of Public University Entrance by invitation is a way to get candidate students from The Senior High Schools that have good achievement, where as the other one open wider access. Nevertheless, the college students who enter through the invitation or non invitation, they don’t necessarily have a better academic achievement or worse than each other. After through the learning process in college, the success of the students are marked with their academic achievement that shown by the index of academic achievement, that if they pass expressed by the status of graduation, cumlaude or not cumlaude. To find out the factors that affect the status of student graduation based on the entrance, the regretion model that can be used is bivariate biner logistic regretion, because it consist of two response variable, the status of graduation and the entrance of the college students. Maximum likelihood estimation is used to estimate the parameter model. To examine the significance of the parameter use Likelihood ratio test and Wald test. Major option and live adress are the significance variables that affect the status of graduation based on the entrance of the college student from predictor variable partially test of school report grades, national test grades, major option, live adress, study method, live cost, students’ relationship with friends and family,and study motivation. Whole test and individual test indicate that major option variable affect the status of graduation based on the entrance significantly.
PEMODELAN PRODUKSI BAWANG MERAH DI JAWA TENGAH DENGAN MENGGUNAKAN HYBRID AUTOREGRESSIVE INTEGRATED MOVING AVERAGE – ADAPTIVE NEURO FUZZY INFERENCE SYSTEM Inas Husna Diarsih; Tarno Tarno; Agus Rusgiyono
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 (666.622 KB) | DOI: 10.14710/j.gauss.v7i3.26661

Abstract

Red onion is one of the strategic horticulture commodities in Indonesia considering its function as the main ingredients of the basic ingredients of Indonesian cuisine. In an effort to increase production to supply national necessary, Central Java as the main center of red onion production should be able to predict the production of several periods ahead to maintain the balance of national production. The purpose of this research is to get the best model to forecast the production of red onion in Central Java by ARIMA, ANFIS, and hybrid ARIMA-ANFIS method. Model accuracy is measured by the smallest RMSE and AIC values. The results show that the best model to modeling red onion production in Central Java is obtained by hybrid ARIMA-ANFIS model which is a combination between SARIMA ([2], 1, [12]) and residual ARIMA using ANFIS model with input et,1, et,2 on the grid partition technique, gbell membership function, and membership number of 2 that produce RMSE 12033 and AIC 21.6634. While ARIMA model yield RMSE 13301,24 and AIC 21,89807 with violation of assumption. And the ANFIS model produces RMSE 14832 and AIC 22,0777. This shows that ARIMA-ANFIS hybrid method is better than ARIMA and ANFIS.Keywords: production of red onion, ARIMA, ANFIS, hybrid ARIMA-ANFIS
IDENTIFIKASI MODEL ANTRIAN BUS RAPID TRANSIT (BRT) PADA HALTE OPERASIONAL BRT SEMARANG Niken Nindyaiswari; Sugito Sugito; Yuciana Wilandari
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 (576.157 KB) | DOI: 10.14710/j.gauss.v4i3.9483

Abstract

The process of a queue is a process related with the attending of customers in a service facility, standing in line waiting for the service while the servers are busy servicing the other customers, the customers will leave the facility after getting the service. This process is usually happened in the public services such as at the operational shelter of Semarang Bus Rapid Transit (BRT) Semarang. BRT Semarang has 4 departure gates and transit bus stop passed by all of the buses. The BRT does not have special track. It has to pass though the same road as the other kinds of buses. As a result there are queues in some crowded BRT shelters especially at the service in the departure and shelters that are passed through by all BRT or tracks. An effective special queue model is needed to make the service in the departure and transit shelter more effective. Based on the result of the analysis the best queue model is at the departure shelter track I, II, III, and IV they use the same models (M/G/1) (GD/∞/∞) and the queue models at the City Hall Transit Shelter are (G/G/1) (GD/∞/∞). Key words: queue process, model of queue, Semarang BRT
ANALISIS FAKTOR-FAKTOR YANG MEMPENGARUHI LAJU PERTUMBUHAN PENDUDUK KOTA SEMARANG TAHUN 2011 MENGGUNAKAN GEOGRAPHICALLY WEIGHTED LOGISTIC REGRESSION Catra Aditya Wisnu Aji; Moch. Abdul Mukid; Hasbi Yasin
Jurnal Gaussian Vol 3, No 2 (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 (669.238 KB) | DOI: 10.14710/j.gauss.v3i2.5902

Abstract

Geographically Weighted Logistic Regression (GWLR) is a local form of logistic regression where geographical factors considered and it is assumed that the Bernoulli distribution of data used to analyze spatial data from non-stationary processes. This research will determine the factors that affect the Population Growth Rate (PGR) in the Semarang city using logistic regression and GWLR with a weighting function of bisquare kernel and gaussian kernel. The result showed that GWLR model with a weighting function of bisquare kernel better than logistic  regression model and GWLR model with a weighting function of gaussian kernel because it has the smallest AIC value and classification accuracy is 87,5%. Factor that have significant effect is the number of couples of childbearing age in the Semarang city.
PEMODELAN GENERALIZED SPACE TIME AUTOREGRESSIVE (GSTAR) SEASONAL PADA DATA CURAH HUJAN EMPAT KABUPATEN DI PROVINSI JAWA TENGAH Eko Siswanto; Hasbi Yasin; Sudarno Sudarno
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 (722.339 KB) | DOI: 10.14710/j.gauss.v8i4.26722

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 volume of rainfall four locations in Jepara Regency, Kudus Regency, Pati Regency, and Grobogan 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 rainfall Pati Regency influenced by the rainfall in other regencies. Keywords: GSTAR, RMSE, Rainfall
ANALISIS PENGELOMPOKAN DAERAH MENGGUNAKAN METODE NON-HIERARCHICAL PARTITIONING K-MEDOIDS DARI HASIL KOMODITAS PERTANIAN TANAMAN PANGAN (Studi Kasus Kabupaten/Kota Se-Jawa Tengah Tahun 2009 – 2013) Etik Setyowati; Agus Rusgiyono; Moch. Abdul Mukid
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 (371.26 KB) | DOI: 10.14710/j.gauss.v4i4.10137

Abstract

Non-Hierarhical K-Medoids Partitioning is a clstering method for classifying objects based on the characteristics possessed by the object, wherein the object k randomly selected to be medoids is the center of the cluster. After medoids selected then other objects that have similarities with medoids made in one cluster. Medoids is the object which is considered to represent a cluster. Similarity between objects is calculated using euclidean distance. One application grouping method Non-Hierarhical K-Medoids Partitioning is to classify District in Central Java is based on the production of rice and pulses. Grouping Regency / City in Central Java using Non-Hierarhical Partitioning K-Medoids obtained information that rice production by Regency / City in Central Java can be grouped into seven clusters, but because of a case in 2010 and in 2011 the number of clusters that formed are two clusters, while the production of food crops by Regency / City in Central Java can be grouped into two clusters.Keywords: k-medoids, Non-Hierarhical, Euclidean distance, Similarities.
PENDETEKSIAN INFLUENTIAL OBSERVATION PADA MODEL REGRESI LINIER MULTIVARIAT MENGGUNAKAN JARAK COOK TERGENERALISASI (STUDI KASUS INDIKATOR PENDIDIKAN PROVINSI JAWA TENGAH TAHUN 2010) Puti Cresti Ekacitta; Diah Safitri; Triastuti Wuryandari
Jurnal Gaussian Vol 1, No 1 (2012): 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 (570.668 KB) | DOI: 10.14710/j.gauss.v1i1.906

Abstract

Multivariate linear regression model is regression model with one or more response variable and one or more predictor variable, with each response variable are mutually. In multivariate linear regression model sometimes often found Influential Observation. Influential Observation give most contributing in estimating regression coefficient. For detection Influential Observation on multivariate linear regression model is used Generalized Cook’s Distance. The aim of this research is to detection any or not any Influential Observation on multivariate linear regression model of education indicator in Central Java Province with response variable are Gross Participation Rate (APK), School Participation Rate (APS), and Pure Participation Number (APM) and predictor variable is percentage of population aged 10 years and over who graduated from junior high school. Result from this research  can be explained that if the percentage of population aged 10 years and over who graduated from junior high school increase one percent, it will have an impact on increasing gross participation rate the junior high school is 1.7849 % , increasing school participation rate is 1.6275 % and   increasing pure participation number is 1.3712 %. Also, from this results were obtained two observations are included Influential observation. Elimination of the two observations are included Influential observation in the multivariate linear regression model of education indicators in Central Java, affects the regression coefficients change only and does not have a major impact on the closeness of the relationship between response variables and predictor variables in the multivariate.
ANALISIS FAKTOR-FAKTOR YANG MEMPENGARUHI KEPUTUSAN PENGGUNAAN TRANSPORTASI PRIBADI PADA MAHASISWA MENGGUNAKAN PENDEKATAN PARTIAL LEAST SQUARE (Studi Kasus pada Universitas Diponegoro Semarang) Martyanto Tedjo; Sugito Sugito; Suparti Suparti
Jurnal Gaussian Vol 6, No 2 (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 (637.66 KB) | DOI: 10.14710/j.gauss.v6i2.16950

Abstract

The process of structural development in developing countries is a must. Each sector that developed is related to one another. These sectors associated with the supporting factor named transport, means transport has a vital and strategic functions in the development of other sectors. Education is one of the construction sector that growing rapidly, especially in big cities, and transportation is one of the factors supporting it: since schools and universities is one of the important generator of domestic transportation network. Each university holds up to tens of thousands of new college students every year. In this point, the transport activity in big cities is becoming increasingly complex, due to the increase in the private transportation is not matched by the increase in roads, causing congestion. Factors that influence the decision of the use of private transport on the student comprehensively analyzed using structural equation based on the variance, Partial Least Square (PLS). PLS is a powerful analytical method, though it’s not based on many assumptions (soft model), for example, the multivariate normal assumptions, it can use nominal scale up to ratios, as well as the sample size shouldn’t be large. PLS estimates the model  od relationship between latent variables and also latent variables with the indicator. Based on the analysis we concluded that the decision on the use in private transportations of Diponegoro University students affected by a combination of latent variables such time management, cost, physical, social interaction, and the intervening variable perception of 68.28%.Keywords: transportation, using of private transportation, Partial Least Square (PLS) 
PENENTUAN MODEL DAN PENGUKURAN KINERJA SISTEM PELAYANAN PT. BANK NEGARA INDONESIA (PERSERO) Tbk. KANTOR LAYANAN TEMBALANG Masfuhurrizqi Iman; Sugito Sugito; 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 (394.961 KB) | DOI: 10.14710/j.gauss.v3i4.8085

Abstract

PT. Bank Negara Indonesia (Persero) Tbk. Tembalang Services Office is a provider of service facilities engaged in the financial sector. As a service facilities provider, queue problem is a problem that occurs absolute and must be considered. The queuing situation occurs because the number of customers in a service facility that exceeds the capacity available to perform such services. At PT. Bank Negara Indonesia (Persero) Tbk. Tembalang Services Office, the queue occurs both at the Teller and Customer Service. After analysis, the best model of a queuing system at the Teller is (M/M/3):(GD:∞:∞), while the best model of queuing system in the Customer Service section is (M/M/2):(GD:∞:∞). The model can be concluded that the queue system available in PT. Bank Negara Indonesia (Persero) Tbk. Tembalang Services office is optimal. Keywords : PT. Bank Negara Indonesia (Persero) Tbk. Tembalang Services Office, queuing system, Teller, Customer Service
ANALISIS LAPANGAN PEKERJAAN UTAMA DI JAWA TENGAH BERDASARKAN GRAFIK BIPLOT SQRT (SQUARE ROOT BIPLOT) Anik Nurul Aini; Diah Safitri; Abdul Hoyyi
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 (467.328 KB) | DOI: 10.14710/j.gauss.v5i1.10911

Abstract

Biplot analysis is one of the methods of descriptive statistical analysis that can present data of the n objects which p variables into a two-dimensional graph. Biplot has several types according to the scale of α used. There are three scales α which is often used in the biplot analysis, that are α = 0, α = 0,5 and α = 1. Biplot with α = 1 is called the RMP biplot (Row Matric Preserving). Biplot with α = 0 is called CMP biplot (Column Matric Preserving). While biplot with α = 0,5 called SQRT biplot (Square Root Biplot). Biplot with a scale of α = 0,5 is the best biplot to describe a data, because it make a graph between variable and object spread evenly. This study aims to create a SQRT biplot amount of population aged 15 years and over who worked according to district/city and major employment opportunities in Central Java. Biplot chart shows areas that have similar characteristics with the closest Euclidean distance. The diversity of characteristics is indicated by the length of the vector, the longest vector contained in the agricultural sector. Based on the biplot analysis in this study, it was obtained that the goodness size biplot is equal to 64,19958%. Keywords: Biplot, Singular Value Decomposition, Jobs, SQRT, Square Root Biplot

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