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Wardhani Utami Dewi
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dewiutamiwardhani@gmail.com
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scncstatistics@gmail.com
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Jl. Ki Hajar Dewantara No.116, Iringmulyo, Metro Timur, Kota Metro, Lampung 34111
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INDONESIA
Sciencestatistics: Journal of Statistics, Probability, and Its Application
Published by Universitas Muhammadiyah Metro
ISSN : 29642884     EISSN : 29639875     DOI : https://doi.org/10.24127
Core Subject : Science, Education,
Computer Science & IT Decision Sciences, Operations Research & Management Mathematics
Sciencestatistics: Journal of Statistics, Probability, and Its Application is an Open Access journal in the field of statistical inference, experimental design and analysis, survey methods and analysis, research operations, data mining, statistical modeling, statistical updating, time series and econometrics, multivariate analysis, statistics education, simulation and modeling, numerical analysis, algebra, combinatorics, and applied mathematics.
Arjuna Subject : Matematika - Statistik dan Probabilitas
Articles 5 Documents
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Search results for , issue "Vol 1 No 2 (2023): JULY" : 5 Documents clear
Goodness Of Fit Test In Structural Equation Modeling with Unweighted Least Square (ULS) Estimation Method Ani Amanathi; Eri Setiawan; Mustofa Usman
Sciencestatistics: Journal of Statistics, Probability, and Its Application Vol 1 No 2 (2023): JULY
Publisher : Universitas Muhammadiyah Metro

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Abstract

Structural equation model (SEM) is a multivariate analysis method that is used to describe a linear relationship simultaneously between indicator variables and latent variables. There are several estimation methods in SEM, one of them is Unweighted Least Square (ULS). The method doesn‟t have specific assumptions about the distribution of variables. This study aims to estimate the model using the ULS method and see the influence of employee competency variables and library facilities on the quality of service at the University of Lampung library. Survey of quality of service in the library of Lampung University is used in the research. Based on the results of the study, it is found that from the three suitability tests, namely the overall model test, the structural model test and the measurement model test using ULS estimation give good results in explaining the compatibility between the model and observation results.
Log-Linear Model on Categorical Data of HIV Cases Wardhani Utami Dewi; Warsono Warsono
Sciencestatistics: Journal of Statistics, Probability, and Its Application Vol 1 No 2 (2023): JULY
Publisher : Universitas Muhammadiyah Metro

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Abstract

Categorical data is widely used in social, health, educational and psychological research. A contingency table is a form of presenting this data. One of them is about cases of being infected with the HIV virus. The log-linear model is an alternative for analyzing categorical data. In this study, HIV cases will be analyzed using a log-linear model grouped by gender, age and province. Apart from that, several log-linear models will be formed and the best model will be selected based on the likelihood ratio (G^2) statistical test. According to the results of the analysis and consideration of model complexity, (JK*P, JK*U, P*U) is the best model and fits the data because the p-value = 0.517 is greater than the real level α = 0.05. This means that the interaction between gender, age and province is significant. Studies and explanations about the HIV virus show that individuals between the ages of 25-49 years are more at risk of being infected with the virus. Examined by gender group, women were most infected with the virus, namely 513 people. Apart from that, West Papua is the province with the highest number of HIV infections compared to Maluku and North Maluku
Bayesian Structural Time Series Model for Forecasting the Composite Stock Price Index in Indonesia Indah Suciati; Mustofa Usman
Sciencestatistics: Journal of Statistics, Probability, and Its Application Vol 1 No 2 (2023): JULY
Publisher : Universitas Muhammadiyah Metro

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Abstract

One of the models that can be used to predict time series data is the Bayesian Structural Time Series (BSTS) model. The BSTS model is a more modern model and can handle data movement better. In the BSTS model, the Markov Chain Monte Carlo (MCMC) sampling algorithm is used to simulate the posterior distribution, which smoothes the forecasting results over a large number of potential models using Bayesian averaging models. The purpose of this study was to obtain the best BSTS model for Composite Stock Price Index (CSPI) data in Indonesia based on the state component and the number of MCMC iterations, and obtain forecasting results for CSPI value in Indonesia for the next 24 months, namely the period July 2023 to June 2024. The results obtained are based on a comparison of the R-square values in the model, the BSTS model with local linear trend and seasonal state components, and the number of MCMC iterations n = 5 00 is the best BSTS model that can be used for forecasting the CSPI value in Indonesia with an R-square value of 99.96%. The results of forecasting the CSPI value in Indonesia for the period July 2023 to June 2024 range from 6589 to 6760, with the lowest forecasting value in October 2023 and the highest in March 2023.
Maximum Likelihood Estimation Approach using the CB-SEM Method: Case Study of Service Quality Putri Meyla Oktavia; Eri Setiawan; Nusyirwan Nusyirwan; Netti Herawati
Sciencestatistics: Journal of Statistics, Probability, and Its Application Vol 1 No 2 (2023): JULY
Publisher : Universitas Muhammadiyah Metro

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Abstract

The purpose of this study to analyze the service level, satisfaction and loyalty of Sariringgung Beach visitors.Covarian based approach to estimatemaximum likelihood method in the service levelto the satisfaction and loyalty of visitorstourism area of Sariringgung Beach is used. The results of this study indicate that the direct effect of service level to satisfaction is 77%, service level to loyalty is 75%. Whereas the indirect effect of service level on loyalty through satisfaction is 38,5%. Then the total effect of service level on customer loyalty through satisfaction is 73,5%.
Artificial Neural Network (ANN) Classification: Titanic Passenger Safety Juanda Juanda; Khoirin Nisa
Sciencestatistics: Journal of Statistics, Probability, and Its Application Vol 1 No 2 (2023): JULY
Publisher : Universitas Muhammadiyah Metro

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Abstract

Scientific and technological innovation has always been the main driver of economic growth and social progress. The rapid development of technology and advances in the internet have made it possible to disseminate information and interact more easily. With the rapid development of technology, a lot of information is shared every second, resulting in big data in terms of different, complex variables. ANN is the result of work in the computer field that is inspired by the capabilities of the human brain which consists of biological neural networks. In recent years, the use of artificial neural networks (ANN) has increased. The research carried out aims to analyze the survival capabilities of Titanic passengers who experienced an accident while sailing and sank. This research uses initial data of 1309 observations with 14 variables. From the research results, 2 hidden variables are the most accurate with an accuracy of 80.5%, compared to the number of hidden variables of 3 (79%) and 4 (79%). So it can be concluded that the number of hidden variables with the same number of hidden screens does not have a significant difference in accuracy

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