Awaliyah, Wahyu Nurlaila (2022) Bayesian Survival Mixture Model Terhadap Ibu Hamil Yang Terinfeksi Covid-19 Di Rsud Dr. R. Sosodoro Djatikoesoemo Bojonegoro. Other thesis, Institut Teknologi Sepuluh Nopember.
|
Text
06211840000058-Undergraduate_Thesis.pdf Restricted to Repository staff only Download (4MB) | Request a copy |
Abstract
World Health Organization (WHO) telah menyatakan Covid-19 sebagai pandemi global sejak awal tahun 2020 lalu. Wanita yang sedang hamil atau baru saja hamil meningkatkan risiko keparahan gejala Covid-19 jika dibandingkan dengan wanita yang tidak hamil. Selain itu juga meningkatkan risiko kelahiran prematur, lahir mati, maupun komplikasi kehamilan lainnya. Salah satu analisis statistika yang berkaitan dengan ketahanan hidup adalah analisis survival. Analisis survival digunakan untuk menganalisis faktor yang mempengaruhi lama rawat inap ibu hamil yang terinfeksi Covid-19 di RSUD Dr. R. Sosodoro Djatikoesoemo Bojonegoro dengan menimbang terjadinya mixture distribution. Oleh karena adanya distribusi khusus pada lama waktu perawatan ibu hamil yang terinfeksi Covid-19, maka estimasi parameter dilakukan dengan pendekatan Bayesian. Penelitian ini membagi lama rawat inap ibu hamil ke dalam 2 komponen mixture, komponen 1 adalah ibu hamil yang lebih cepat sembuh dan komponen 2 adalah ibu hamil yang lebih lambat sembuh. Pola waktu survival (lama rawat inap) ibu hamil yang terinfeksi Covid-19 mengikuti distribusi Weibull 2 parameter. Hasil penelitian menunjukkan bahwa besar kontribusi dari masing-masing komponen terhadap model laju kesembuhan adalah sebesar 65% dan 35%. Model survival cox proportional hazard dibentuk dengan mengikuti pola dari distribusi Weibull 2 parameter dengan masing-masing komponen memiliki parameter yang berbeda. Model komponen 1 memiliki 4 faktor yang berpengaruh dan pada model komponen 2 terdapat 4 faktor yang berpengaruh. Faktor yang signifikan pada model laju kesembuhan ibu hamil adalah usia ibu hamil, usia kehamilan, pekerjaan, jenis terapi, dan tingkat gejala Covid-19.
==============================================================================================================================
The World Health Organization (WHO) has declared Covid-19 a global pandemic since early 2020. Women who are pregnant or have recently become pregnant are at increased risk for the severity of COVID-19 symptoms when compared to women who are not pregnant. It also increases the risk of premature birth, stillbirth, and pregnancy complications. One of the statistical analyzes related to survival is survival analysis. Survival analysis is used to analyze the factors that influence the length of stay of pregnant women infected with Covid-19 at the Dr R. Sosodoro Djatikoesoemo Bojonegoro by considering the occurrence of the mixture distribution. Due to the unique distribution of the length of time for care for pregnant women infected with Covid-19, the parameter estimation is carried out using a Bayesian approach. This study divides the length of stay for pregnant women into 2 mixture components, component 1 is pregnant women who recover faster and component 2 is pregnant women who recover more slowly. The pattern of survival time (length of hospitalisation) of pregnant women infected with Covid-19 follows a 2-parameter Weibull distribution. The results showed that the contribution of each component to the cure rate model was 65% and 35%. Cox proportional hazard survival model was formed by following the pattern of the 2-parameter Weibull distribution with each component having different parameters. Component model 1 has 4 influencing factors and in the component 2 model, there are 4 influencing factors. Significant factors in the recovery rate model for pregnant women are the age of the pregnant woman, gestational age, occupation, type of therapy, and level of symptoms of Covid-19.
| Item Type: | Thesis (Other) |
|---|---|
| Additional Information: | RSSt 519.542 Awa b-1 2022 |
| Uncontrolled Keywords: | Bayesian. Covid-19. Ibu Hamil. Survival Mixture Model. Bayesian. Covid-19. Pregnant Women. Survival Mixture Model. |
| Subjects: | H Social Sciences > HA Statistics |
| Divisions: | Faculty of Science and Data Analytics (SCIENTICS) > Statistics > 49201-(S1) Undergraduate Thesis |
| Depositing User: | Mr. Marsudiyana - |
| Date Deposited: | 11 Jun 2026 01:16 |
| Last Modified: | 11 Jun 2026 01:16 |
| URI: | http://repository.its.ac.id/id/eprint/133711 |
Actions (login required)
![]() |
View Item |
