Suharningtyas, Githa Andani (2019) Model Ketahanan Hidup Pasien Tuberkulosis Menggunakan Metode Bayesian Hierarki. Other thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
Analisis ketahanan Hidup adalah suatu himpunan dari prosedur statistika untuk menganalisis data waktu tahan hidup pasien terhadap suatu penyakit di mana variabel respon diakibatkan karena variabel prediktor yang berpengaruh. Pada Tugas Akhir ini, analisis ketahanan hidup dilakukan pada pasien penderita Tuberkulosis di rumah sakit Dr. Moh. Anwar 2017-2018. Penyebaran peyakit Tuberkulosis yang menyerang kekebalan tubuh manusia disebabkan oleh 2 faktor yaitu faktor individu dan faktor lingkungan, karena bertambahnya jumlah penderita penyakit Tuberkulosis (individu) berkorelasi dengan lingkungan tempat tinggal (Kecamatan). Data yang mengandung individu dan kecamatan adalah data berstruktur hierarki. Selanjutnya, dilakukan estimasi parameter dari distribusi Weibull dengan menggunakan metode Bayesian Hierarki menggunakan metode Markov Chain Monte Carlo (MCMC) dengan Gibbs Sampling. Berdasarkan hasil estimasi diperoleh β_1= 0.0052, β_2=-0.034, β_3= 0.0517, β_4= -0.126, dan γ_11=-0.003, diketahui bahwa faktor risiko terbesar pada variabel umur dan pekerjaan. Kemudian menentukan dependensi korelasi pada efek random spasial dari daerah-daerah yang saling berdekatan menggunakan autokorelasi spasial yang dinyatakan melalui sebuah matriks pembobotan dengan bantuan aplikasi Geoda. Dalam menentukan ada atau tidaknya pengaruh antar Kecamatan terhadap angka kejadian Tuberkulosis maka digunakan Statistik Uji Moran’s I yang menunjukkan nilai statistik Moran’s I sebesar -0,297 dan nilai Z-value sebesar 0,2862 sehingga disimpulkan bahwa tidak terdapat pengaruh lokasi atau tidak berkelompok setiap kecamtan pada kejadian Tuberkulosis.
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Survival analysis a result of calculated statistics to analysis patients' survival data for a disease in which the response variable is caused by an independent variable that influences. In this Final Project, survival analysis was performed in patients with Tuberculosis in Dr. Moh. Anwar. The spread of Tuberculosis disease that attacks the human immune system is caused by two factors, namely individual factors and environmental factors, because the increasing number of people with Tuberculosis (individuals) correlates with the living environment (District). Data containing individuals and sub-districts is hierarchical data structure. Furthermore, parameter estimation of the Weibull distribution is performed using the Bayesian Hierarchy method using the Markov Chain Monte Carlo (MCMC) method with Gibbs Sampling. Based on the estimation results obtained β_1= 0.0052, β_2=-0.034, β_3= 0.0517, β_4= -0.126, and γ_11=-0.003, it is known that the biggest risk factor is the age and occupational variables. Then determine the correlation dependencies on spatial random effects of adjacent areas using spatial autocorrelation expressed through a weighting matrix with the help of the Geoda application. In determining whether or not there is influence between sub-districts on the number of Tuberculosis Events, Moran's I Test Statistics are used which show the statistical value of Moran's I is -0.297 and Z-value is 0.2862 so it is concluded that there is no significant influence on the incidence of Tuberculosis.
| Item Type: | Thesis (Other) |
|---|---|
| Additional Information: | RSMa 519.542 Suh m-1 2019 |
| Uncontrolled Keywords: | Analisis Ketahahan Hidup, Bayesian Hierarki, Moran’s I, MCMC, Gibbs Sampling, WinBUGS, Geoda |
| Subjects: | Q Science Q Science > QA Mathematics Q Science > QA Mathematics > QA274.2 Stochastic analysis Q Science > QA Mathematics > QA274.7 Markov processes--Mathematical models. Q Science > QA Mathematics > QA279.5 Bayesian statistical decision theory. Q Science > QA Mathematics > QA76.9 Computer algorithms. Virtual Reality. Computer simulation. Q Science > QA Mathematics > QA278 Cluster Analysis. Multivariate analysis. Correspondence analysis (Statistics) |
| Divisions: | Faculty of Mathematics and Science > Mathematics > 44201-(S1) Undergraduate Thesis |
| Depositing User: | Githa Andani Suharningtyas |
| Date Deposited: | 22 Apr 2024 03:46 |
| Last Modified: | 22 Apr 2024 03:46 |
| URI: | http://repository.its.ac.id/id/eprint/64515 |
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