Anasi, Raras (2018) Pemodelan Jumlah Kasus HIV dan AIDS Di Jawa Timur Menggunakan Bivariate Generalized Poisson Regression. Undergraduate thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
Human Immunodefficiency Virus (HIV) merupakan virus yang menyerang sistem imum dan menjadi penyebab penyakit AIDS.(Acquired Imunnodeficiency Syndrome). Berdasarkan laporan Kementerian Kesehatan RI triwulan IV (2016), Jawa Timur merupakan wilayah dengan jumlah penderita HIV tertinggi kedua dengan 6513kasus. Penelitian ini menggunakan metode Bivariate Generalized Poisson Regression untuk melihat faktor-faktor yang mempengaruhi jumlah kasus HIV di Jawa Timur tahun 2016. Bivariate Generalized Poisson Regression merupakan pengembangan dari regresi Bivariate Poisson Regression dan salah satu metode untuk menannggulangi overdispersi data. Berdasarkan hasil analisis Bivariate Generalized Poisson Regression dengan dengan kriteria AIC diketahui bahwa model terbaik memuat keseluruhan variabel prediktor. Faktor yang mempengaruhi jumlah kasus HIV di Jawa Timur tahun 2016 adalah rasio layanan PDP, rasio layanan IMS, persentase kemiskinan, presentase pengguna kontrasepsi jenis kondom dan rasio layanan KT. Sedangkan faktor yang mempengaruhi jumlah kasus AIDS yaitu rasio layanan PDP, rasio layanan IMS, persentase kemiskinan, presentase pengguna kontrasepsi jenis kondom dan rasio layanan KT===========================================================================================Human Immunodefficiency Virus (HIV) is a kind of virus that attacs the immunity system and causes AID(Acquired Imunnodeficiency Syndrome). According to the statement report from the Ministry of Health in the fourth quarter of 2016, East Java is the second highest number oh HIV in infected with 6513. This study uses the the Bivariate Generalized Poisson Regression method to see the factors affecting the number of HIV and AIDS in East Java. Bivariate Generalized Poisson Regression is an expansion of Bivariate Poisson Regression and one of methods that overcome the overdispersion/underdispersion of data. Based on the result of Bivariate Generalized Poisson Regression analysis with AICc criteria is known that the best model contains the whole predictor variable. Factors that affecting the number of HIV cases in East Java are the ratio of PDP facilities, the ratio of IMS facilities, the percentage of poverty, the percentage of condom users, and the ratio of KT facilities. Meanwhile the factors that affecting the number of AIDS cases in East Java are the ratio of PDP facilities, the ratio of IMS facilities, the percentage of poverty, the percentage of condom users, and the ratio of KT facilities.
| Item Type: | Thesis (Undergraduate) |
|---|---|
| Uncontrolled Keywords: | AIDS, Bivariate Generalized Poisson Regression, HIV,Overdispersi |
| Subjects: | Q Science > QA Mathematics > QA278.2 Regression Analysis. Logistic regression |
| Divisions: | Faculty of Mathematics, Computation, and Data Science > Statistics > 49201-(S1) Undergraduate Thesis |
| Depositing User: | Raras Anasi |
| Date Deposited: | 18 Jul 2021 22:25 |
| Last Modified: | 18 Jul 2021 22:25 |
| URI: | http://repository.its.ac.id/id/eprint/57517 |
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