Agus Rusgiyono
Departemen Statistika, Fakultas Sains Dan Matematika, Universitas Diponegoro

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Journal : Jurnal Gaussian

ANALISIS FAKTOR-FAKTOR YANG MEMPENGARUHI KEMISKINAN DI JAWA TENGAH MENGGUNAKAN MODEL GALAT SPASIAL Octafinnanda Ummu Fairuzdhiya; Rita Rahmawati; 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 (652.239 KB) | DOI: 10.14710/j.gauss.v3i4.8089

Abstract

Poverty is one of problems in developing country like Indonesia. From year to year, poverty in Central Java has decreased. This study is aimed to know the poverty model in Central Java by using Spatial Error Model. This research uses data from the number of poor people in Central Java in 2012. Spatial Error Model is a spatial method that showed spatial autocorrelation in the error. In Spatial Error Model, there are spatial dependency effect and spatial heterogenity. The variables that significantly affect the number of poor people in Central Java through Spatial Error Model are the percentage of 10 years old–over population with the highest education is primary school ( X2) and the number of households that have access to reliable drinking water (X3). This Spatial Error Model results R2 are 75,39% with the AIC are 63,36. It is better than regression model of Ordinary Least Square (OLS) which produces 66,3% of R2 with AIC are 69,286. It showed the poverty model in Central Java by using Spatial Error Model is better than regression model of Ordinary Least Square (OLS) and in OLS assumption of homoskedasticity not significant. Keywords: Poverty, Regression, Ordinary Least Square, Spastial Error Model
PENGGUNAAN METODE PERAMALAN KOMBINASI TREND DETERMINISTIK DAN STOKASTIK PADA DATA JUMLAH PENUMPANG KERETA API (Studi Kasus : KA Argo Muria) Titis Nur Utami; Abdul Hoyyi; Agus Rusgiyono
Jurnal Gaussian Vol 6, No 1 (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 (768.04 KB) | DOI: 10.14710/j.gauss.v6i1.14776

Abstract

The amount of the data of KA Argo Muria indicates the improve in every year during Ied mubarak day. Ied Mubarak day follows the Hijriyah calender, this is inditates that there is case effect of variation on the calender. The aims of this research is to predict the amount of the KA Argo Mulia passanger of destination of Semarang – Jakarta for 12 periodes in the future by using forecasting time series model of variation calender. The data used mounthly amount data  KA Argo Mulia  at PT KAI DAOP IV Semarang in the periode of January 2014 until Desember 2015. The result of the data analysis shows significant variable toward the model is   and the model of  Autoregressive Integrated Moving Average (ARIMA) (1,0,0). Based on the result of forecasting  out-sample data, is gained Mean Absolute Percentage Error (MAPE) is 1,8089 % which indicates that the result of forecasting is very good.Keywords: deterministic trend, calender variation, time series, stochastic model, dummy regression.
PEMODELAN VARIABEL-VARIABEL PENGELUARAN RUMAH TANGGA UNTUK KONSUMSI TELUR ATAU SUSU DI KABUPATEN MAGELANG MENGGUNAKAN REGRESI TOBIT Viliyan Indaka Ardhi; Agus Rusgiyono; 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 (564.495 KB) | DOI: 10.14710/j.gauss.v4i4.10242

Abstract

Censored data is the data on a dependent variable of which most of the observations are worth less than or equal to zero while others have a certain value or more than zero. Tobit regression model is a statistical model that can overcome the problems in which many independent variables is zero or called data censored. In this  research, modeling eggs or milk consumption in Magelang is analyzed using tobit regression. The data used   in this research is secondary data derived from Susenas Data Magelang regency 2013. The concluding results of the final modeling shows that the educational level of householder, the amount of expenditure for food in a month, the number of children in the household and the householder’s profession give significant effect on    household expenditures for the consumption of eggs or milk with a coefficient determination of  is 60,31%. While the remaining 39,69 % is effected by other variables is not examined in this study such as the appetite of consumers and  health factors.              Keywords: Consumption of  Eggs or Milk, Tobit Regression, Censored Data
PENERAPAN METODE STRUCTURAL EQUATION MODELING UNTUK ANALISIS KEPUASAN PENGGUNA SISTEM INFORMASI AKADEMIK TERHADAP KUALITAS WEBSITE (Studi Kasus pada Website sia.undip.ac.id) Enggar Nur Sasongko; Mustafid Mustafid; Agus Rusgiyono
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 (681.357 KB) | DOI: 10.14710/j.gauss.v5i3.14695

Abstract

Quality of website has an important role in giving effect to the website user's satisfaction. The quality of a website is measured by the adjusted WebQual dimensions include the dimensions of the system, dimension of information, dimension of interaction and dimension of services. Structural Equation Modeling is a method that used to examine complicated correlation simultaneously consisting of dependent variables and independent variables. This research aims to apply Structural Equation Modeling and Importance Performance Analysis methods in determining the influence of website quality factors on user satisfaction of academics Information System's website, and to find the performance of variables that need to be improved. This research is conducted at the University of Diponegoro, involving 200 students from Diponegoro University as the respondents. From the test of overall models, it obtained Goodness of Fit with the value of Chi Square = 68.748 and RMSEA = 0.084. From the analysis, it can be concluded that the dimension of interaction has the effect of 35%, dimension of information in amount of 35%, the dimension of service is 22.1%, and the dimensions of system in amount of 8.7%. And variables that need to improve performance are ease of website to be accessed's variable, variable of detail information, and ease of PBM evaluation's variable. Keywords: website quality, user satisfaction, Structural Equation Modeling
IDENTIFIKASI CURAH HUJAN EKSTREM DI KOTA SEMARANG MENGGUNAKAN ESTIMASI PARAMETER MOMEN PROBABILITAS TERBOBOTI PADA NILAI EKSTREM TERAMPAT (Studi Kasus Data Curah Hujan Dasarian Kota Semarang Tahun 1990-2013) Annisa Rahmawati; Agus Rusgiyono; Triastuti Wuryandari
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 (553.692 KB) | DOI: 10.14710/j.gauss.v3i4.8067

Abstract

The methods used to analyze extreme rainfall is the Extreme Value Theory (EVT). One of the approaches of EVT is the Block Maxima (BM) which follows the distribution of Generalized Extreme Value (GEV). In this study, the dasarian rainfall data of 1990-2013 in the Semarang City is divided based on block monthly and the month examined are October, November, December, January, February, March and April. The resulted blocks are 24 with 3 observations each block. Estimated parameter of form, location and scale are obtained by using the method of Probability Weight Moments (PWM). The result of this study is January has the greatest occurrence chance of extreme value with the value of estimated parameter of form 0,3840564, location 138,8152989 and scale 68,6067117. In addition, the alleged maximum value of dasarian rainfall obtained in a period of 2, 3, 4, 5 and 6 years are 243,45753 mm, 308,23559 mm, 357,26996 mm, 397,96557 mm and 433,28889 mm. Keywords: rainfall, Extreme Value Theory, Block Maxima, Generalized Extreme Value, Probability Weight Moments
PEMODELAN PERTUMBUHAN EKONOMI JAWA TENGAH MENGGUNAKAN PENDEKATAN LEAST ABSOLUTE SHRINKAGE AND SELECTION OPERATOR (LASSO) Feby Kurniawati Heru Prabowo; Yuciana Wilandari; Agus Rusgiyono
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 (542.859 KB) | DOI: 10.14710/j.gauss.v4i4.10220

Abstract

The economic growth recently become more important because of its implementation widely, the economic growth concept is a measure of country or  regional economy valuation. The economic growth data in this research that is measured by Gross Regional Domestic Product (GRDP) are susceptible of   multicollinearity. Multicollinearity become a problem in regression analysis, especially in Ordinary Least Square (OLS) because it causes the regression coefficient estimates become not efficient. One of method to overcome multicollinearity is using Least Absolute Shrinkage and Selection Operator (LASSO). LASSO is a shrinkage method to estimate regression coefficients by minimazing residual sum of squares subject to a constraint. Because of that constraint, LASSO can shrinks coefficients towards zero or set them to exactly zero so it can do  variable selection too. Based on Variance Inflation Factor (VIF), there are high correlations between predictor variables, so there is multicollinearity in growth economic data of Jawa Tengah 2013 if we use OLS. In this research, LASSO shrinks eleven coefficients estimator of predictor variables to exactly zero, so that variables considered to have not a significant influence toward model. Keywords : LASSO, Multicollinearity, Shrinkage, Gross Regional Domestic Product (GRDP)
PREDIKSI CURAH HUJAN DENGAN METODE KALMAN FILTER (Studi Kasus di Kota Semarang Tahun 2012) Tika Dhiyani Mirawati; Hasbi Yasin; Agus Rusgiyono
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 (668.3 KB) | DOI: 10.14710/j.gauss.v2i3.3669

Abstract

The rainfall data is very interesting to be studied because it is constitutes one of the biggest factor that influence the climate on a region and human life sector. In this studies, the rainfall prediction is utilized by Kalman Filter method. The implementation of Kalman Filter analysis in this research is used for modelling and forecasting rainfall in Semarang city. This method provide a recursive solution to minimize error. Kalman Filter consists of state equation and observation equation. The forecasting result in 2012 showed that the prediction is close to the current data whereas in 2013 it increase which the maximum rainfall is 406 mm happening in February and the minimum rainfall is 35 mm happening in July. Overall, the average rainfall in 2013 at Semarang city is 196,25 mm
KLASIFIKASI STATUS KERJA PADA ANGKATAN KERJA KOTA SEMARANG TAHUN 2014 MENGGUNAKAN METODE CHAID DAN CART Novie Eriska Aritonang; Agus Rusgiyono; Rita Rahmawati
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 (311.148 KB) | DOI: 10.14710/j.gauss.v5i1.11045

Abstract

The growth of  labor will increase along with increasing population. Increasing the number of this labor of course going to have an impact on his status, whether employ or unemployed. The method can be used to classify the status of the labor is CHAID (Chi-squared Automatic Interaction Detection) and CART (Classification and Regression Trees). Both of these methods aim to identify factors that influence employment status. These methods will be applied for Semarang labor data in 2014. Based on CHAID method, the factors that affect the status of the labor is gender, age and status of the completeness of a life partner with accuracy classification results amounted to 72.63%. Factors that affect the status of the labor force with the CART method is gender, age, educational status, and the status of the completeness of a life partner with the accuracy of the classification is 72.79%. Based on proportion test, these methods are same of doing classification employment status.Keywords: Labor, Classification, CHAID, CART, Accuracy of classification
PENERAPAN RESPONSE BASED UNIT SEGMENTATION IN PARTIAL LEAST SQUARE (REBUS-PLS) UNTUK ANALISIS DAN PENGELOMPOKAN WILAYAH (Studi Kasus: Kesehatan Lingkungan Perumahan di Provinsi Jawa Tengah) Febriana Sulistya Pratiwi; Sudarno Sudarno; Agus Rusgiyono
Jurnal Gaussian Vol 9, No 3 (2020): 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.v9i3.28927

Abstract

Residental environmental health is a complex problem that depends on several dimensions. One of the statistical method that can be used to analyze the relation between complex dimensions is Structural Equation Modeling (SEM) with a variant/component based approach or Partial Least Square. The purpose of this study is to develop a structural model of the relation between household economy, education, housing facilities, and residental environmental health in Central Java Province in 2018 based on 12 valid and reliable indicators. In the structural equation model there is a significant positive effect path that is the influence of household economy towards education and towards housing facilities, and influence housing facility on the residential environment health. In SEM analysis it is generally assumed that the data taken comes from a homogeneous population but often the data consists of several segments. Therefore, we need a method to detect heterogeneity problems, namely Response Based Unit Segmentation in Partial Least Square (REBUS-PLS). Based on the dendogram produced, by forming 2 classes/segments,  values as the accuracy of the prediction model on the local model had a higher value (except  values for Education in local model 2) than  values on the global model. In addition, the Goodnes of Fit value as a measure of model suitability for each local model is also had a higher value, so that it indicates the goodness of the model in the local model is better than the global model.Keywords: environmental health, SEM, PLS, REBUS-PLS
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.
Co-Authors Abdul Hoyi Abdul Hoyyi Agustina Sunarwatiningsih Alan Prahutama Alan Prahutama Andreanto Andreanto Anggita, Esta Dewi Anifa Anifa Anindita Nur Safira ANNISA RAHMAWATI Annisa Rahmawati Arief Rachman Hakim Aulia Putri Andana Aulia Rahmatun Nisa Bagus Arya Saputra Bayu Heryadi Wicaksono Bellina Ayu Rinni Besya Salsabilla Azani Arif Bramaditya Swarasmaradhana Budi Warsito Dede Zumrohtuliyosi Dermawanti Dermawanti Desy Tresnowati Hardi Di Asih I Maruddani Diah Safitri Diah Safitri Dian Mariana L Manullang Dini Anggreani Diyah Rahayu Ningsih Dwi Asti Rakhmawati Dwi Ispriyansti Dwi Ispriyanti Eis Kartika Dewi Ely Fitria Rifkhatussa'diyah Elyasa, Fatiya Rahmita Enggar Nur Sasongko Etik Setyowati Etik Setyowati, Etik Farisiyah Fitriani fatimah Fatimah Febriana Sulistya Pratiwi Feby Kurniawati Heru Prabowo Fitriani Fitriani Hana Hayati Hanik Malikhatin Hanik Rosyidah, Hanik Hasbi Yasin Hasbi Yasin Hildawati Hildawati Hindun Habibatul Mubaroroh Ika Chandra Nurhayati Ilham Muhammad Imam Desla Siena Inas Husna Diarsih Iwan Ali Sofwan Kevin Togos Parningotan Marpaung Listifadah Listifadah M. Afif Amirillah M. Atma Adhyaksa Marthin Nosry Mooy Maryam Jamilah An Hasibuan Maulana Taufan Permana Merlia Yustiti Moch. Abdul Mukid Moch. Abdul Mukid Muhammad Rizki Muhammad Taufan Mustafid Mustafid Mustafid Mustafid Mustofa, Achmad Nabila Chairunnisa Nor Hamidah Noveda Mulya Wibowo Novie Eriska Aritonang Nur Khofifah Nur Walidaini Octafinnanda Ummu Fairuzdhiya Puji Retnowati Puspita Kartikasari Putri Fajar Utami Rengganis Purwakinanti Revaldo Mario Ria Sulistyo Yuliani Riana Ikadianti Riszki Bella Primasari Rita Rahmawati Rita Rahmawati Rizal Yunianto Ghofar Rizky Aditya Akbar Rosita Wahyuningtyas Rukun Santoso Salsabila Rizkia Gusman Setiyowati, Eka Shella Faiz Rohmana Siti Lis Ina Atul Hidayah Sudargo Sudarno Sudarno Sudarno Sudarno Sudarno Sudarno Sudarno Sudarno Sugito - Sugito Sugito Sugito Sugito Suparti Suparti Suparti Suparti Susi Ekawati sutimin sutimin Tarno Tarno Tarno Tarno Tarno Tarno Tatik Widiharih Tatik Widiharih Tiani Wahyu Utami Tika Dhiyani Mirawati Tika Nur Resa Utami, Tika Nur Resa Titis Nur Utami Tri Ernayanti Tri Yani Elisabeth Nababan Triastuti Wuryandari Triastuti Wuryandari Tyas Ayu Prasanti Tyas Estiningrum Ulfi Nur Alifah Ungu Siwi Maharunti Uswatun Hasanah Vierga Dea Margaretha Sinaga Viliyan Indaka Ardhi Winastiti, Lugas Putranti Yogi Isna Hartanto Yuciana Wilandari Yuciana Wilandari Yuciana Wilandari