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

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (926.554 KB) | DOI: 10.19184/jid.v19i1.6997


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

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (469.156 KB) | DOI: 10.19184/jid.v20i2.9862


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.