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All Journal Jurnal Ilmu Dasar Jurnal Gaussian KADIKMA BERKALA SAINSTEK Prosiding Seminar Matematika dan Pendidikan Matematik UNEJ e-Proceeding International Conference on Mathematics and Science Education of Universitas Pendidikan Indonesia Majalah Ilmiah Matematika dan Statistika (MIMS) JURNAL BIOSHELL Pancaran Pendidikan

I Made Tirta

Program Studi Magister Matematika, FMIPA, Universitas Jember

Author-ID : 403778

Agriculture, Biological Sciences & Forestry Humanities Biochemistry, Genetics & Molecular Biology Chemistry Control & Systems Engineering Education Immunology & microbiology Languange, Linguistic, Communication & Media Mathematics Physics Other

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Covariance Based approach SEM with Bollen-Stine Estimation (Case Study Analysis of The Effect of Teacher and Principal Competence on Achievement of National Standards) Kasmuri Kasmuri; I Made Tirta; Yuliani Setia Dewi
Jurnal ILMU DASAR Vol 16 No 2 (2015)
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Jember

Applications of covariance Based SEM (CB-SEM) generally use the maximum likelihood, based upon the assumption on the normal distribution of data. One alternative that could be applied if the data were not normally distributed is estimation using Bollen-Stine bootstrap approach. In this study, the method is applied to reveal the influence of teacher competence, the principal competence, to the value of achievement of national education standards in secondary schools in Banyuwangi.The objective of this paper was to determine and analyze the relationship and to know the the most dominant indicators of measure latent variables between the the principal, teachers competences on national standards of educational attainment in secondary schools in Banyuwangi. The results indicate that all of the indicator of variables are valid and reliable to measure corresponding latent variables. Each latent variable has the most dominan indicator. For the principal competence latent variables the most dominant indicator is the entrepreneurial competence, for teachers competency the most dominant is personal competence, whereas for national education standards, the most dominant standard of facilities. Principal competence has indirect influence on national education standard achievement, but directly affect the competence of teachers. Teacher competence directly influence national education standards.Keywords: Power Competence Teachers, Competence Principal, National Education Standards, covariance Based SEM, Bollen-Stine Bootstrap Estimates

Discriminant AnalysisFor Cluster Validation In A Case Study of District Grouping In Jember Regency Based On Poverty Fikriana Nur Istiqomah; Made Tirta; Dian Anggareni
Jurnal ILMU DASAR Vol 20 No 2 (2019)
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Jember

Cluster validation is a procedure to evaluate the results of cluster analysis quantitively and objectively on a data. The validation process is very important to get the results of a good and appropriate grouping. In the validation process, the author uses internal validation, stability, and discriminant analysis test. This study aims to obtain validation results from the hierarchy and kmeans method. This data grouping uses “iris” simulation data, which results from the grouping method used can be applied to the original data to see which vaidation method is used for all data and produce an optimal grouping. The result of the study show that in the “iris” data, a single linkage link is an appropriate grouping method because the result of the grouping are optimal for all validations and classification of group members whose groups are significant. In District poverty data in Jember Regency with a single linkage link optimal grouping was obtained and complete linkage links were also used as a method that resulted in optimal groupig for all validation. Cluster validation discriminant analysis test is appropriate for various types of data in general annd shows that single linkage methods are better than other methods for grouping and validation methods for “iris” data and District data in Jember Regency based on variabels of poverty status. Keywords: Cluster Analysis, Diskriminant Analysis, Multivariate Analysis, Validation Cluster.

The Development of Web-based Graphical User Interface for Learning and Fitting Generalized Estimating Equation with Spline Smoothers Made Tirta; Dian Anggraeni
Jurnal ILMU DASAR Vol 19 No 1 (2018)
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Jember

Statistical modeling (regression analyses) have been growing rapidly into various directions to accommodate various data conditions. For longitudinal or repeated measures data, one of the suitable models is GEE (Generalized Estimating Equation). In practice, to do complex modeling such as GEE, the use of statistical software is necessary and it is available on free open source software R. However, GEE modeling on R can only be access through command line interface (CLI), and most practical researchers very much rely on Graphical User Interface (GUI) based statistics software. To make access to GEE (both order 1 and 2) much easier, we developed, using Shiny toolkit, two types of web-based GUI, standard pull down menu type and e-module type (with narrative theories) that can be utilized for learning and fitting GEE. This paper discusses the features of the interfaces and illustrates the use of them. Keywords: longitudinal data, Generalized Estimating Equation (GEE), exponential families, statistical modeling, correlated response, nonparametric, natural splines, shiny toolkit

Structural Equation Modeling of the Factors Affecting the Nutritional Status of Children Under Five in Banyuwangi Region using Recursive (one-way) GSCA I Made Tirta; Nawal Ika Susanti; Yuliani Setia Dewi
Jurnal ILMU DASAR Vol 16 No 1 (2015)
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Jember

Structural Equation Modeling is one among popular multivariate analysis, especially applied in pschology and marketing. There are two main types of Structural Equation Modeling namely covariance-based or CB-SEM and variance-based or Partial Least Square (PLS)- SEM. Both types have advantages and disadvantage. To overcome its limitation, Generalized Structured Component Analysis (GSCA) was then proposed as an extension of PLS-SEM. In estimating the parameters, GSCA uses Alternating Least Squares (ALS) and in estimating the standard error of the parameter estimates it uses the bootstrap method. In this paper, GSCA is applied to study the causality model of Infant nutritional status, in relation with socio-economic status and infantcare status in Banyuwangi Region. The results show that both socio-economic and infantcare status have significant positive influence on infant nutritional status.Keywords: Alternating least square, generalized structural component analysis, nutritional status of infants, structural equation modelling

The Efficiency of First (GEE1) and Second (GEE2) Order “Generalized Estimating Equations” for Longitudinal Data Rizka Dwi Hidayati; I Made Tirta; Yuliani Setia Dewi
Jurnal ILMU DASAR Vol 15 No 1 (2014)
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Jember

The approach of GEE focuses on a linear model for the mean of the observations in the cluster without full specification the distribution of full-on observation. GEE is a marginal model where is not based on the full likelihood of the response, but only based on the relationship between the mean (first moment) and variance (second moment) as well as the correlation matrix. The advantage of GEE is that the mean of parameter are estimated consistently regardless whether the correlation structure is specified correctly or not, as long as the mean has the correct specifications. However, the efficiency may be reduced when the working correlation structure is wrong. GEE was designed to focus on the marginal mean and correlation structure as nuisiance treat. Implementation of GEE is usually limited to the number of working correlation structure (eg AR-1, exchangeable, independent, m-dependent and unstructured). To increase the efficiency of the GEE, has introduced a variation called the Generalized Estimating Equations order 2 (GEE2). GEE2 has been introduced to overcome the problem that considers correlation GEE as nuisiance, by applying the second equation to estimate covariance parameters and solved simultaneously with the first equation. This study used simulation data which are designed based on the the AR-1 and Exchangeable correlation structure, then estimation are done using theAR1 and exchangeable. For GEE2, estimation done by adding model for correlation link. The result is a link affects the efficiency of the model correlation is shown with standard error values generated by GEE2 method is smaller than the GEE method.

Analysis of the Death Risk of Covid-19 Patients Using Extended Cox model Cyndy Romarizka; Mohamat Fatekurohman; I Made Tirta
Jurnal ILMU DASAR Vol 24 No 1 (2023)
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/jid.v24i1.33074

Globally, in 2021, there were 170,051,718 COVID-19 cases and 3,540,437 patients who died. The high mortality rate of patients infected with COVID-19 gives an idea to research the analysis of the factors that influence the death of Covid-19 patients. The data used in this study is data on Covid-19 patients obtained from the Mexican Government, with response variables namely time and status and predictor variables, namely patient laboratory results in the form of a history of illness that has been suffered by Covid-19 patients so that they adopt the extended model to evaluate the data. The data in this study are heterogeneous and large in number so that data clustering is carried out into 3 clusters, namely low emergency clusters, medium emergency clusters and high emergency clusters using K-means clustering. Because the study could not find the factors that influence the death of Covid-19 patients, two clusters were chosen, namely the medium emergency cluster and the high emergency cluster. So that the factors that influence the death of Covid-19 patients in the medium emergency cluster are sorted by the highest hazard ratio, namely pneumonia, old age, renal chronic, diabetes, Chronic Obstructive Pulmonary Disease (COPD), immune system, hypertension, cardiovascular, obesity, gender, and asthma. In the high emergency cluster, sorted by the highest hazard ratio is the immune system, renal chronic, cardiovascular, COPD, tobacco, hypertension, obesity, gender, and pneumonia.

Co-Authors A AsÃ¢Â€Â™ad Agus Isdarmawan Agustina Pradjaningsih Aminatus Sholiha Anak Agung Gede Sugianthara Andina Ishmah Almira, Andina Ishmah Budi Lestari Budi Lestari Cyndy Romarizka Dian Anggareni Dian Anggraeni Dian Anggraeni Erfan Syahuri Fikriana Nur Istiqomah Habibi, Azwar Haeruddin Haeruddin Holipah, Holipah Indriasih Yanuwijaya Istiqomah, Fikriana Nur Kasmuri Kasmuri Kasmuri Kasmuri, Kasmuri Lutfi Ardining Tyas M Fatekurrahman M. Isnaini Marino Marino, Marino Miftahul Ulum Mohamad Fatekurohman Mutiarasari, Yusna Nawal Ika Susanti Nawal Ika Susanti, Nawal Ika Rizka Dwi Hidayati T C P Utama Tika Clarinta Putri Utama Yeni Rismawati Yuliani Setia Dewi

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