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All Journal Media Statistika JURNAL MATEMATIKA STATISTIKA DAN KOMPUTASI CAUCHY: Jurnal Matematika Murni dan Aplikasi Jurnal Sains Matematika dan Statistika Science and Technology Indonesia NUMERICAL (Jurnal Matematika dan Pendidikan Matematika) Jurnal Matematika: MANTIK Jurnal Elementer (Elektro dan Mesin Terapan) Desimal: Jurnal Matematika Syntax Literate: Jurnal Ilmiah Indonesia JWP (Jurnal Wacana Politik) BAREKENG: Jurnal Ilmu Matematika dan Terapan JTAM (Jurnal Teori dan Aplikasi Matematika) Limits: Journal of Mathematics and Its Applications Buletin Ilmiah Nagari Membangun Eksakta : Berkala Ilmiah Bidang MIPA Jurnal Aplikasi Statistika & Komputasi Statistik M A T H L I N E : Jurnal Matematika dan Pendidikan Matematika Jurnal Matematika UNAND Community Development Journal: Jurnal Pengabdian Masyarakat Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika Warta Pengabdian Andalas: Jurnal Ilmiah Pengembangan Dan Penerapan Ipteks Journal of Science and Technology Makara Journal of Health Research Lattice Journal : Journal of Mathematics Education and Applied STATISTIKA Limits: Journal of Mathematics and Its Applications

Yanuar, Ferra

Universitas Andalas

Author-ID : 754057

Agriculture, Biological Sciences & Forestry Humanities Astronomy Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Nursing Physics Public Health Social Sciences Transportation Veterinary Other

Published : 114 Documents Claim Missing Document

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Articles

Title

Comparison of Two Priors in Bayesian Estimation for Parameter of Weibull Distribution Yanuar, Ferra; Yozza, Hazmira; Rescha, Ratna Vrima
Science and Technology Indonesia Vol 4 No 3 (2019): July
Publisher : ARTS Publishing

This present study purposes to conduct Bayesian inference for scale parameters, denoted by , from Weibull distribution. The prior distribution chosen in this study is the prior conjugate, that is inverse gamma and non-informative prior, namely Jeffreys? prior. This research also aims to study several theoretical properties of posterior distribution based on prior used and then implement it to generated data and make comparison between both Bayes estimator as well. The method used to evaluate the best estimator is based on the smallest Mean Square Error (MSE). This study proved that Bayes estimator using conjugate prior produces parameter value that is better estimate than the non-informative prior since it produces smaller MSE value, for condition scale parameter value more than one based on analytic and simulation study. Meanwhile for scale parameter value less than one,  it could not yielded the good estimated value.

The Property of Continuity And Positively Definite Characteristic Function of Compound Poisson Distribution As The Sum of Geometric Distribution Sherli Yurinanda; Ferra Yanuar; Dodi Devianto
Science and Technology Indonesia Vol. 3 No. 2 (2018): April
Publisher : Research Center of Inorganic Materials and Coordination Complexes, FMIPA Universitas Sriwijaya

The compound Poisson distribution as the sum of independent and identically random variables from geometric distribution is characterized by using characteristic function. The characteristic function of this compound distribution is obtained by Laplace-Stieltjes transform. It is provided a characterization of this compound distribution employing the properties of characteristic function as continuous and positively definite function.

Simulation Study of Autocorrelated Error Using Bayesian Quantile Regression Nayla Desviona; Ferra Yanuar
Science and Technology Indonesia Vol. 5 No. 3 (2020): July
Publisher : Research Center of Inorganic Materials and Coordination Complexes, FMIPA Universitas Sriwijaya

The purpose of this study is to compare the ability of the Classical Quantile Regression method and the Bayesian Quantile Regression method in estimating models that contain autocorrelated error problems using simulation studies. In the quantile regression approach, the data response is divided into several pieces or quantiles conditions on indicator variables. Then, The parameter model is estimated for each selected quantiles. The parameters are estimated using conditional quantile functions obtained by minimizing absolute asymmetric errors. In the Bayesian quantile regression method, the data error is assumed to be asymmetric Laplace distribution. The Bayesian approach for quantile regression uses the Markov Chain Monte Carlo Method with the Gibbs sample algorithm to produce a converging posterior mean. The best method for estimating parameter is the method that produces the smallest absolute value of bias and the smallest confidence interval. This study resulted that the Bayesian Quantile method produces smaller absolute bias values and confidence intervals than the quantile regression method. These results proved that the Bayesian Quantile Regression method tends to produce better estimate values than the Quantile Regression method in the case of autocorrelation errors. Keywords: Quantile Regression Method, Bayesian Quantile Regression Method, Confidence Interval, Autocorrelation.

Quantile Regression Approach to Model Censored Data Sarmada Sarmada; Ferra Yanuar
Science and Technology Indonesia Vol. 5 No. 3 (2020): July
Publisher : Research Center of Inorganic Materials and Coordination Complexes, FMIPA Universitas Sriwijaya

Abstract The censored quantile regression model is derived from the censored model. This method is used to overcome problems in modeling censored data as well as to overcome the assumptions of linear models that are not met. The purpose of this study is to compare the results of the analysis of the quantile regression method with the censored quantile regression method for censored data. Both methods were applied to generated data of 150, 500, and 3000 sample size. The best model is then chosen based on the smallest absolute bias and the smallest standard error as an indicator of the goodness of the model. This study proves that the censored quantile regression method tends to produce smaller absolute bias and a smaller standard error than the quantile regression method for all three group data specified. Thus it can be concluded that the censored quantile regression method could result in acceptable model for censored data. Keywords: Censored data; quantile regression; quantile regression censored; standard error; absolute bias.

Cement Compressive Strength Control Using CUSUM and MCUSUM Control Chart Surya Puspita Sari; Ferra Yanuar; Dodi Devianto
Science and Technology Indonesia Vol. 5 No. 2 (2020): April
Publisher : Research Center of Inorganic Materials and Coordination Complexes, FMIPA Universitas Sriwijaya

Compressive strength is one of the test factors used to determine whether cement production is in a controlled state or not. Portland type composite cement or PCC is the cement that is widely used in infrastructure development. The Cement of 3-days compressive strength, 7-days compressive strength, and 28-days compressive strength are the variables that will be controlled in this study. The normal distribution test and correlation test show that the data on each variable is normally distributed, and each variable has a strong correlation. Univariate cement control using the cumulative sum control chart (CUSUM) and multivariate control using a multivariate cumulative sum (MCUSUM) control chart is performed to obtain the best control results. Correlated variables show that control using a multivariate control chart results in fewer outs of control observations compared to a univariate control chart. This explains that the MCUSUM control chart is more sensitive than the CUSUM control chart in controlling observations of data out of control.

The Comparison of WLS and DWLS Estimation Methods in SEM to Construct Health Behavior Model Ferra Yanuar; Fadilla Nisa Uttaqi; Aidinil Zetra; Izzati Rahmi; Dodi Devianto
Science and Technology Indonesia Vol. 7 No. 2 (2022): April
Publisher : Research Center of Inorganic Materials and Coordination Complexes, FMIPA Universitas Sriwijaya

It is unknown how reliable various point estimates, standard errors, and standard several test statistics are for standardized SEM parameters when categorical data used or misspecified models are present. This paper discusses the comparison between WLS and DWLS for examining hypothesized relations among ordinal variables. In SEM, the polychoric correlation is employed either in WLS or DWLS. This study constructs the Health behavior model as an endogenous latent variable in which exogenous latent variables are Perceived susceptibility and Health motivation. All indicators are in categorical types. Thus, data are not multivariate normal, or the model could be misspecified. This study compares the values of standard deviation and coefficient determination to determine a better model. The criteria for the goodness of fit for the overall model are based on RMSEA, CFI, and TLI values. This present study found that the WLS estimator method resulted in better values than DWLS’s.

Spatial Autoregressive Quantile Regression with Application on Open Unemployment Data Ferra Yanuar; Tasya Abrari; Izzati Rahmi HG; Aidinil Zetra
Science and Technology Indonesia Vol. 8 No. 2 (2023): April
Publisher : Research Center of Inorganic Materials and Coordination Complexes, FMIPA Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26554/sti.2023.8.2.321-329

The Open Unemployment Level (OUL) is the percentage of the unemployed to the total labor force. One of the provinces with the highest OUL score in Indonesia is West Java Province. If an object of observation is affected by spatial effects, namely spatial dependence and spatial diversity, then the regression model used is the Spatial Autoregressive (SAR) model. Quantile regression minimizes absolute weighted residuals that are not symmetrical. It is perfect for use on data distribution that is not normally distributed, dense at the ends of the data distribution, or there are outliers. The Spatial Autoregressive Quantile Regression (SARQR) is a model that combines spatial autoregressive models with quantile regression. This research used the data regarding OUR in West Java in 2020 from the Central Bureau of Statistics. This study develops to modeling the Open Unemployment Level in all province in Indonesia using modified spatial autoregressive model with the quantile regression approach. This study compares the estimation results based on SAR and SARQR models to obtain an acceptable model. In this study, it was found that the SARQR model is better than SAR at dealing with the problems of dependency and diversity in spatial data modeling and is not easily affected by the presence of outlier data.

Modeling of Human Development Index Using Bayesian Spatial Autoregressive Approach Yanuar, Ferra; Wulandari, Sintya; Asdi, Yudiantri; Zetra, Aidinil; Haripamyu
Science and Technology Indonesia Vol. 10 No. 1 (2025): January
Publisher : Research Center of Inorganic Materials and Coordination Complexes, FMIPA Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26554/sti.2025.10.1.72-79

Spatial regression analysis is a technique employed to examine the relationship between independent and dependent variables in datasets that exhibit regional neighborhood influences or spatial effects. When a spatial effect exists for the independent variable, the Spatial Autoregressive (SAR) regression can be utilized. The Maximum Likelihood Estimation (MLE) is a commonly used parameter estimator for SAR. However, due to the limitations of MLE, the Bayesian method provides an alternative approach for parameter estimation. This study compares the results of SAR estimations using both MLE and Bayesian methods to determine the most accurate estimation model. Both methods were implemented in this research to model the factors affecting the Human Development Index (HDI) in East Java Province for the year 2022. The findings indicate that the Bayesian SAR offers a superior proposed model compared to the MLE SAR. The factors influencing the HDI in East Java Province in 2022 include poverty, per capita expenditure, and the presence of an upper middle-class manufacturing industry.

Co-Authors Abdi Mulya Admi Nazra AMALIA DWI PUTRI Amalia Dwi Putri ANGGUN CITRA DELIMA ANNISA RAHMADIAH Arfarani Rosalindari Arrival Rince Putri Asdi, Yudiantri Astari Rahmadita ATIKAH RAHMAH PUTRI Azmi Arsa Bahri, Susila Baqi, Ahmad Iqbal Boby Canigia Budi Rudianto Budi Rudianto Catrin Muharisa Cichi Chelchillya Candra Cichi Chelchillya Candra Cici Saputri Cintya Mukti Cintya Mukti Des Welyyanti Deva, Athifa Salsabila Devianto, Dodi Dila Mulya Dina Monica DINIE ANEFI HAJARA Efendi Efendi Elfa Rafulta Ermanely Ermanely Fadilla Nisa Uttaqi Fajriyah, Rahmatika Farhah Anggana Febriyuni, Rahmi Firdawati, Firdawati FITARI RESMALANI Fitri Aulia FITRI SABRINA Gusmanely Z Harahap, Vika Pradinda Haripamyu Haripamyu Hasibuan, Lilis Harianti Hazmira Yozza Helmi, Monika Rianti Ihsan Kamal Ikhlas Pratama Sandi Indah Pratiwi Izzati Rahmi HG Izzati Rahmi HG Jenizon Jenizon Kamarni, Neng Kartini Aboo Talib @Khalid Khatimah, Havifah Husnatul Lilis Harianti Hasibuan Livia Amanda M. Pio Hidayatullah M. Rizki Oktavian Maiyastri Maiyastri, Maiyastri Majbur, Ridha Fauza Mardha Tillah Mawanda Almuhayar MEILINA DINIARI Melisa Febriyana Mesi Oktafia Meutia Fikhri MIFTAHUL JANNAH HB Mira Serma Teti Mita Oktaviani Muhammad Iqbal Muhammad Qolbi Shobri Muharisa, Catrin Mutiara Fara Nabilla Nadia Cindi Eka Putri Nadiah Ramadhani NADYA PUTRI ALISYA Nadya Putri Alisya Narwen Narwen Nayla Desviona Nova Noliza Bakar Noverina Alfiany Nurmaylina Zaja Qalbi, Latifatul Radhiatul Husna RAHMI HG, IZZATI Rahmi, Fatihatur Ramadhani, Eza Syafri Religea Reza Putri Rescha, Ratna Vrima Resti Mustika Sari Resti Nanda Yani Riau, Ninda Permata Ridhatul Ilahi Riri Lestari Riri Lestari Rudiyanto Rudiyanto, Rudiyanto SAIDAH . Sani, Ridha Fadhila Saputri, Ovi Delviyanti Sari, Putri Trisna Sarmada Sarmada Sarmada, Sarmada Selfinia, Selfinia SHINTA MUTIA KARNEVA Shinta Wulandari SHINTA YULIANA Silvia . SILVIA YUNANDA Sisi Andriani Siti Juriah SITI LATHIFAH IRMA SUMINDANG YUZAN Surya Puspita Sari, Surya Puspita Susi Marisa Syafwan, Mahdhivan Syauqi, Irfan Tari Adriana Musana Tasya Abrari Tasya Abrari Uswatul Hasanah VIKI ANDRIANI Widya Wijayanti WINDA LIDYA Winda Oktari WULANDARI, FRILIANDA Wulandari, Sintya wulandari, sisca Yanita Yanita Yosika Putri Yulmiati Yulmiati Yurinanda, Sherli Zahratul Aini Zetra, Aidinil Zetra, Aidinil Zulakmal, Zulakmal Zulhazizah .

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