Bayesian Reversible Jump Markov Chain Monte Carlo (RJMCMC) Untuk Pemodelan Mixture Survival (Studi Kasus: Lama Pernikahan Para Pihak Yang Mendaftarkan Gugatan Perceraian Di Pengadilan Agama Kabupaten Malang Tahun 2014) = Bayesian Reversible Jump Markov Chain Monte Carlo (RJMCMC) For Modelling Mixture Survival (Case Studies: Long Marriage of The Parties that Registers a Lawsuit Divorces in The Religious Court Kabupaten Malang Year 2014)

Rejki, Najihatur (2015) Bayesian Reversible Jump Markov Chain Monte Carlo (RJMCMC) Untuk Pemodelan Mixture Survival (Studi Kasus: Lama Pernikahan Para Pihak Yang Mendaftarkan Gugatan Perceraian Di Pengadilan Agama Kabupaten Malang Tahun 2014) = Bayesian Reversible Jump Markov Chain Monte Carlo (RJMCMC) For Modelling Mixture Survival (Case Studies: Long Marriage of The Parties that Registers a Lawsuit Divorces in The Religious Court Kabupaten Malang Year 2014). Masters thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Analisis survival merupakan metode statistika yang tepat untuk
menganalisis data waktu tempuh suatu objek sampai terjadinya suatu peristiwa atau
kejadian tertentu terhadap objek tersebut. Banyaknya kasus perceraian di
Pengadilan Agama (PA) merupakan masalah yang cukup mengkhawatirkan di
masyarakat, pengamatan tentang lama suatu pernikahan dapat dipertahankan
merupakan fenomena survival ini. Pengamatan dilakukan pada para pihak yang
mendaftarkan gugatan perceraiannya di PA Kabupaten Malang, sebagai unit
penelitian. Penelitian ini mendemonstrasikan kemampuan pemodelan mixture
survival dalam suatu cox proportional hazard yang dipadukan dengan cara estimasi
parameternya menggunakan perpaduan antara Bayesian dan metode reversible
jump markov chain monte carlo (RJMCMC) pada data survival yang mempunyai
pola multimodal. RJMCMC dapat membantu memodelkan permasalahan mixture
secara bersamaan dengan penentuan banyaknya komponen penyusunan mixture
yang optimal. Hasil pemodelan dan analisis menunjukkan bahwa model survival
pernikahan di area PA Kabupaten Malang berdasarkan regresi cox proportional
hazard dipengaruhi oleh faktor umur penggugat dan tergugat, pendidikan
penggugat dan tergugat, pekerjaan penggugat dan tergugat, jumlah anak, dan alasan
perceraian. Sedangkan berdasarkan pemodelan mixture regresi survival terdiri atas
4 komponen mixture dengan faktor yang mempengaruhi berbeda-beda sesuai
dengan komponen mixture-nya.
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Survival analysis is a statistical method that is appropriate to analyze the
data takes about an object until the occurrence of a certain event or events of the
object. The number of divorce cases in the Religious Court is an alarming problem
in the community, the old observation about a marriage can be maintained this is a
survival phenomenon. Observations were made on the parties who filed a divorce
in Religious Court Malang, a research unit. This study demonstrates mixture
modeling capabilities survival in a cox proportional hazards combined with the
parameter estimation method using a combination of Bayesian and methods of
reversible jump Markov chain Monte Carlo (RJMCMC) on survival data having a
multimodal pattern. RJMCMC can help model the problems mixture
simultaneously with the determination of the number of components of the optimal
mixture preparation. Modeling and analysis of the results showed that the survival
model of marriage in the Religious Court area Malang by Cox proportional hazards
regression was influenced by the plaintiff and the defendant's age, education
plaintiff and the defendant, the plaintiff and the defendant's occupation, number of
children, and the reason for the divorce. While based on survival regression
modeling mixture consists of four components mixture with factors affecting vary
in accordance with its mixture components.

Item Type: Thesis (Masters)
Additional Information: RTSt 519.542 Rej b
Uncontrolled Keywords: Analisis Survival, Cox Proportional Hazard, Lama Pernikahan, Mixture Regresi, Reversible Jump Markov Chain Monte Carlo (RJMCMC), Age of Marriage, Cox Proportional Hazard, Mixture Regression, Reversible Jump Markov Chain Monte Carlo (RJMCMC), Survival Analysis
Subjects: Q Science > QA Mathematics > QA274.7 Markov processes--Mathematical models.
Divisions: Faculty of Mathematics and Science > Statistics > 49101-(S2) Master Thesis
Depositing User: ansi aflacha
Date Deposited: 26 Mar 2018 03:48
Last Modified: 24 Aug 2018 06:32
URI: http://repository.its.ac.id/id/eprint/51632

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