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Journal : Majalah Ilmiah Matematika dan Statistika (MIMS)

ANALISIS STRUCTURAL EQUATION MODELING (SEM) DENGAN MULTIPLE GROUP MENGGUNAKAN R Holipah, Holipah; Tirta, I Made; Anggraeni, Dian
Majalah Ilmiah Matematika dan Statistika Vol 19 No 2 (2019): Majalah Ilmiah Matematika dan Statistika
Publisher : Jurusan Matematika FMIPA Universitas Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/mims.v19i2.17272

Abstract

Structural Equation Model (SEM) is a statistical technique with simultaneous processing involves measurement errors, indicator variables, and latent variables. SEM is used to test hypotheses that state the relationships between latent variables when latent variables have been assessed through each of the indicator variables. Multiple Group SEM is a basic model analysis that uses more than one sample. This analysis aims to determine whether the components or models of measurement and structural models are invariant for the two sample groups. In this study, the data generated by some requirements. First, the data generated with sample size n = 250. The first generated data is homogeneous data where the measurement model is the same as the structural model in group 1 and group 2, while the second data is non-homogeneous data where the measurement model and the structural model in group 1 and group 2 is not the same. The data was analyzed using the help of the lavaan package available in R to obtain SEM estimation results and Goodness of Fit Model from some data that was formed. From the results of the merger of the two groups, it shows that the invariant of the two models with the largest df (63) which is Fit Mean model states the simplest model. However, the smallest df (48) with Fit.configural model states the most complex model. Keywords: SEM, Multiple Group, R Program
ANALISIS DISKRIMINAN UNTUK VALIDASI CLUSTER PADA STUDI KASUS PENGELOMPOKAN KECAMATAN DI KABUPATEN JEMBER BERDASARKAN STATUS KEMISKINAN Istiqomah, Fikriana Nur; Tirta, I Made; Anggraeni, Dian
Majalah Ilmiah Matematika dan Statistika Vol 18 No 1 (2018): Majalah Ilmiah Matematika dan Statistika
Publisher : Jurusan Matematika FMIPA Universitas Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/mims.v18i1.17239

Abstract

. Cluster validation is a procedure to evaluate the results of cluster analysis quantitatively 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 validation 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 Sub-district poverty data in Jember district with a single linkage link optimal grouping was obtained and complete linkage links were also used as a method that resulted in optimal grouping for all validation. Cluster validation using discriminant analysis test is appropriate for various types of data in general and shows that single linkage methods are better than other methods for grouping and validation methods for “iris” data and Sub-district data in Jember district based on variables of poverty status. Keywords: Cluster Analysis, Diskriminant Analysis, Multivariate Analysis, Validation Cluster
Optimization of Inventory Level to Uncertain Demand Using Bayesian Approach Isnaini, M.; Tirta, I Made; Pradjaningsih, Agustina
Majalah Ilmiah Matematika dan Statistika Vol 16 No 1 (2016): Majalah Ilmiah Matematika dan Statistika
Publisher : Jurusan Matematika FMIPA Universitas Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/mims.v16i1.23734

Abstract

The decision to determine grade of optimum supply on uncertainty demand or mainly unknowing could accomplish with Buyer-approach method.The demand with mainly unknowing can assumed as Poisson distribute.Completion with Buyer-approach method could be starting with count of posterior Gamma have distributed from prior Gamma with α and ß parameter. At the end the result of counting above can compared with proportion between supply and demand until we get a stable-grade of supply.
Analysis of Service Time in The Bank with Exponential Distribution Mutiarasari, Yusna; Tirta, I Made; Pradjaningsih, Agustina
Majalah Ilmiah Matematika dan Statistika Vol 17 No 1 (2017): Majalah Ilmiah Matematika dan Statistika
Publisher : Jurusan Matematika FMIPA Universitas Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/mims.v17i1.23748

Abstract

Exponential distribution is general assumption to describe the distribution of service time for customer. To examine such assumption, the Goodness of Fit Test-Kolmogorov Smirnov is used. To know the condition queue system in BCA will be use some analyze the steady state characteristic measurement of work queue system on different day and hour.