Garuda - Garba Rujukan Digital

p-Index From 2020 - 2025

4.033

P-Index

This Author published in this journals

All Journal Media Statistika MATEMATIKA SAINS DAN MATEMATIKA Jurnal Gaussian Jurnal Statistika Universitas Muhammadiyah Semarang

Agus Rusgiyono

Departemen Statistika, Fakultas Sains Dan Matematika, Universitas Diponegoro

Author-ID : 366013

Decision Sciences, Operations Research & Management Mathematics Other

Published : 107 Documents Claim Missing Document

Claim Missing Document

Articles

3 4 5 6 7

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

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.

PENERAPAN METODE GENERALIZED STRUCTURED COMPONENT ANALYSIS PADA KEPUASAN KONSUMEN (Studi Kasus: Pasien Klinik Q) Farisiyah Fitriani; Agus Rusgiyono; Tatik Widiharih
Jurnal Gaussian Vol 9, No 4 (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.v9i4.29416

Customer satisfaction is used by a company to evaluate products or services whether it is sufficient with customer’s expectations. Satisfaction is influenced by factors that cannot be measured directly are called latent variables and can be measured through indicators used to measure satisfaction with Structural Equation Modeling (SEM). Generalized Structured Component Analysis (GSCA) method is part of a SEM based on a variant that does not require the assumption of a multivariate normal distribution and has a measure overall goodness of fit. The parameters used are factor loading, coefficients parameter, and weight of indicators and estimated with alternating least square. The type of data used primary data from the results of the questionnaire with stratified proportional random sampling and number of samples 286. This research using indicators as measurable variables as many 32 indicators and 8 latent variable. Considering to the evaluation of the structural model, it is found there are 5 variables that influence satisfaction, they are prices, quality yield, cleanliness, doctor's services, and employee services with a large influence of 77.18% and the impact of satisfaction on loyalty is 48.63 %. For the overall goodness of fit measure, it is known that the FIT value is 63.75% and the adjusted FIT (AFIT) value is 63.47%. The goodness of fit (GFI) produced the value in the amount of 96.43%, indicating that the general model has the good level of compatibility.Keywords: Generalized Structured Component Analysis, Structural Equation Modeling, Overall goodness of fit, Alternating Least Square, Stratified Proportional Random Sampling

PENERAPAN ANALISIS KLASTER METODE WARD TERHADAP KABUPATEN/KOTA DI JAWA TENGAH BERDASARKAN PENGGUNA ALAT KONTRASEPSI Yogi Isna Hartanto; Agus Rusgiyono; Triastuti Wuryandari
Jurnal Gaussian Vol 6, No 4 (2017): 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.v6i4.30387

The cluster analysis of the Ward method is a cluster forming method based on minimizing the loss of information due to the incorporation of objects into clusters. An Error Sum of Square (ESS) is used as an objective function. Two objects will be combined if they have the smallest objective function among possibilities. The similarity measure used is the Euclidean distance. In this experiment used data from the number of users of contraceptives in Central Java Province. Contraceptives that can be detected its use is IUD, MOW, MOP, condoms, implants, injections, and pills. The results of cluster analysis of Ward method were obtained as many as 3 clusters. First cluster consists of 9 districts/cities with the number of use of most contraceptives, namely Cilacap, Banyumas, Pati, Pemalang, Tegal, Jepara, Grobogan, Demak, and Semarang City. Second cluster consists of 21 districts/cities with the number of use of medium contraceptives, namely Purbalingga, Banjarnegara, Kendal, Wonogiri, Pekalongan, Blora, Brebes, Kebumen, Wonososbo, Boyolali, Karanganyar, Sragen, Magelang, Klaten, Semarang, Purworejo, Temanggung , Sukorejo, Rembang, Batang, and Kudus. Third cluster consists of 5 districts/cities with the number of use of contraceptives a little, namely Magelang City, Salatiga City, Surakarta City, Pekalongan City, and Tegal City. Keywords: Contraceptives, Cluster Analysis, Ward Methods, Euclidean Distance

ANALISIS PREFERENSI KONSUMEN PENGGUNA JASA MASKAPAI PENERBANGAN UNTUK RUTE SEMARANG-JAKARTA DENGAN METODE CHOICE-BASED CONJOINT (FULL PROFILE) Vierga Dea Margaretha Sinaga; Diah Safitri; Agus Rusgiyono
Jurnal Gaussian Vol 4, No 4 (2015): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Airline services nowadays become one of the highly coveted options by many consumers for long-distance transportation. The increasing numbers of users makes airlines tightly compete each other to attract consumers’ interest. Thus, analysis to consumer preference has always been the starting point in market research as reference in creating new innovation. This research uses the choice-based conjoint analysis with the full profile as method of presentation. Conjoint analysis is a multivariate analysis method that can be used as a measurement for the level of preference. In the instrument, consumers were asked to choose one among three attribute combination of each choice set within 9 choice sets. Utility values were obtained by conditional logic model. The results show that for each attribute the order of preference is Price-Airport tax-Class-Facility. Judging from the value of its usefulness, the most preferred attribute by consumer is Airport tax and that Include is preferably from Exclude. For Price attribute, lower than 500 thousand rupiahs is the most preferred categories among others. In Class attribute, Business is more preferable than other categories. And for Facility attribute, entertainment is the most preferred one of other categories. Keywords: preferences, airlines, choice-based conjoint

PEMODELAN SEMIPARAMETRIC GEOGRAPHICALLY WEIGHTED REGRESSION PADA KASUS PNEUMONIA BALITA PROVINSI JAWA TENGAH Putri Fajar Utami; Agus Rusgiyono; Dwi Ispriyanti
Jurnal Gaussian Vol 10, No 2 (2021): 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.v10i2.30945

Geographical and inter-regional differences have contributed to the diversity of child pneumonia cases in Central Java, so a spatial regression modelling is formed that is called Geographically Weighted Regression (GWR). GWR is a development of linear regression by involving diverse factors geographical location, so that local parameters are produced. Sometimes, there are non-local GWR parameters. To overcome some non-local parameters, Semiparametric Geographically Weighted Regression (SGWR) is formed to develop a GWR model with local and global influences simultaneously. SGWR Model is used to estimate the model of percentage of children with pneumonia in Central Java with population density, average temperature, percentage of children with severe malnutrition, percentage of children with under the red line weight, percentage of households behave in clean and healthy lives, and percentage of children who measles immunized. SGWR models on percentage of children with pneumonia in Central Java produce locally significant variables that is population density, average temperature, and percentage of households behave in clean and healthy lives. Variable that globally significant is percentage of children with severe malnutrition. Based on Akaike Information Criterion (AIC), SGWR is a better model to analize percentage of children with pneumonia in Central Java because of smallest AIC. Keywords: Akaike Information Criterion, Geographically Weighted Regression, Semiparametric Geographically Weighted Regression

IMPLEMENTASI R-SHINY UNTUK ANALISIS BIPLOT KOMPONEN UTAMA (Studi Kasus: Penggunaan Alat Kontrasepsi pada Peserta Aktif KB di Provinsi Jawa Tengah Tahun 2019) Andreanto Andreanto; Hasbi Yasin; Agus Rusgiyono
Jurnal Gaussian Vol 10, No 4 (2021): 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.v10i4.33097

The population problem is a fairly complex and complicated problem. Therefore, Indonesia seeks to control the birth rate with the Family Planning program. The implementation of this program can be evaluated through statistical data. The statistical analysis used is biplot principal component analysis to see the relationship between districts/cities in choosing the contraceptive device/method used, the variance of each contraceptive device/method, the correlation between contraceptive devices/methods, and the superiority value of the contraceptive device/method in the population. each district/city. The problem with performing the analysis is the limitations of easy-to-use open source software. As with R, users must understand writing code to perform data analysis. Therefore, to perform a biplot analysis of the principal components, an RShiny application has been created using RStudio. The R-Shiny that has been made has many advantages, including complete results which include data display, data transformation, SVD matrix, to graphs along with plot graph interpretation. The results of the principal component biplot analysis using R-Shiny with α =1 have the advantage of a good principal component biplot, which is 95.63%. This shows that the biplot interpretation of the main components produced can be explained well the relationship between the district/city and the contraceptive methods/devices used.

KLASTERISASI PROVINSI DI INDONESIA BERDASARKAN FAKTOR PENYEBARAN COVID-19 MENGGUNAKAN MODEL-BASED CLUSTERING t-MULTIVARIAT Nor Hamidah; Rukun Santoso; Agus Rusgiyono
Jurnal Gaussian Vol 11, No 1 (2022): 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.v11i1.33999

The spread of Covid-19 had a significant impact in all sectors. Enforcement policies from the government that are appropriate with the conditions for the spread of the virus that are needed to prevent a bigger impact. Clusteritation by province based on data on the spread of Covid-19 is important for the government to set appropriate policies in order to prevent the spread of Covid-19. The data used include data on population density, testing rate, proportion of population 50 years and over, and proportion of population diligently hand-washing in each province. The data factors for the spread of Covid-19 tend to overlap and there are outliers in the data which causes the data not normally distributed. In this study, Model-Based Clustering t-multivariate was used for data clustering. The results show that using Integrated Completed Likelihood, two groups of optimal cluster were obtained. The second cluster has a higher risk of spreading Covid-19 than the first cluster. Keywords : Covid-19, Clustering, Model-Based Clustering t-Multivariat

MODEL REGRESI MENGGUNAKAN LEAST ABSOLUTE SHRINKAGE AND SELECTION OPERATOR (LASSO) PADA DATA BANYAKNYA GIZI BURUK KABUPATEN/KOTA DI JAWA TENGAH Aulia Putri Andana; Diah Safitri; Agus Rusgiyono
Jurnal Gaussian Vol 6, No 1 (2017): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Gizi buruk adalah bentuk terparah dari proses terjadinya kekurangan gizi yang menahun. Gizi buruk dipengaruhi oleh banyak faktor yang saling terkait. Dalam penelitian ini, dilakukan pemodelan dari faktor-faktor yang mempengaruhi gizi buruk menggunakan metode Least Absolute Shrinkage Selection and Operator (LASSO) dengan algoritma Least Angle Regression (LARS) karena pada faktor-faktor yang mempengaruhi gizi buruk terdeteksi multikolinearitas. LASSO menyusutkan koefisien regresi dari variabel bebas yang memiliki korelasi tinggi menjadi tepat pada nol atau mendekati nol. Koefisien LASSO dicari dengan menggunakan pemrograman kuadratik sehingga digunakan algoritma LARS yang lebih efisien dalam komputasi LASSO. Berdasarkan analisis yang telah dilakukan, model LASSO pada data gizi buruk Kabupaten/Kota di Jawa Tengah tahun 2014 diperoleh pada tahap kedua saat nilai s=0.02 dengan nilai MSE sebesar 0,82977. Disimpulkan bahwa variabel bayi (0-6 Bulan) yang diberi ASI Eksklusif, rumah tangga berperilaku hidup bersih dan sehat, bayi yang mendapat imunisasi Hepatitis B, bayi yang mendapat imunisasi DPT-HB3, rumah dengan sanitasi yang layak, dan rumah dengan air minum sesuai dengan syarat kesehatan berpengaruh terhadap bayi gizi buruk di Jawa Tengah tahun 2014. Kata Kunci: gizi buruk, multikolinearitas, LASSO, LARS

PEMODELAN REGRESI HECKIT UNTUK KONSUMSI SUSU DI PROVINSI JAWA TENGAH Dwi Asti Rakhmawati; Dwi Ispriyansti; Agus Rusgiyono
Jurnal Gaussian Vol 6, No 3 (2017): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

In multiple regression if the response variable is dummy variable then it can not be used because it will produce biased and inconsistent estimator. The appropriate method for binary response variables is Heckit Regression. Estimation of Heckit Regression parameter using Two Step Method of Procurement is the selection equation and the result equation. In the selection equation will get new variable that is Invers Mills Ratio. While in Equation Result of new variable of Inverse Mills Ratio is added as independent variable along with other independent variable. Heckit Regression method is applied to household milk consume data obtained from 2015 SUSENAS results as many as 201 households. The response variable used is household expenditure for milk consumption. The independent variables used are the working status of the head of the household, the last education of the head of the household, the number of household members, the number of toddler age in the family and the income of the household.Keywords: Multiple Regression, OLS, Heckit Regression, Two Step Procedure, Milk consumption expenditure.

PENENTUAN FAKTOR-FAKTOR YANG MEMPENGARUHI INTENSITAS CURAH HUJAN DENGAN ANALISIS DISKRIMINAN GANDA DAN REGRESI LOGISTIK MULTINOMIAL (Studi Kasus: Data Curah Hujan Kota Semarang dari Stasiun Meteorologi Maritim Tanjung Emas Periode Oktober 2018 – Maret 2019) Shella Faiz Rohmana; Agus Rusgiyono; Sugito Sugito
Jurnal Gaussian Vol 8, No 3 (2019): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Meteorologist develop rainfall forecasting methods to obtain better and more accurate rainfall information. One of them is the research of grid data and the method of grouping rainfall. According to BMKG, rainfall is classified into light, medium, and heavy rain. This study aims to determine the factors that influencing rainfall grouping using multiple discriminant analysis with a stepwise selection method. This study uses the daily climate data of Semarang City for period of October 2018 to March 2019. Based on its partial F value, the wind speed variable is eliminated so the significant variable on rainfall grouping are air temperature, air humidity, and wind direction. This analysis produces discriminant scores obtained from linear combinations between discriminant weights and observation values of significant independent variable. The classification procedure is based on the discriminant score each observations compared to cutting score resulted in classification accuracy of 62.89%. Multinomial logistic regression analysis is used to determine the effect of independent variables on rainfall intensity using the odds ratio. This analysis produces an estimate of the conditional probability of each group using significant independent variables are air temperature, air humidity, wind speed, and wind direction. The classification procedure is based on the largest conditional probability value between rainfall groups resulted in classification accuracy of 69.80%. Keywords: multiple discriminant analysis, multinomial logistic regresion, classification accuracy, rainfall

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

Title

Found 107 Documents
Search

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Title Search

Found 107 Documents Search

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Title

Found 107 Documents
Search