Pemodelan Generalized Additive Model For Location, Scale, and Shape (Gamlss) Dengan Pemulusan Locally Estimated Scatterplot Smoothing (Loess) pada Kasus Hiv/Aids Di Jawa Timur
Pemodelan Generalized Additive Model For Location, Scale, and Shape (Gamlss) Dengan Pemulusan Locally Estimated Scatterplot Smoothing (Loess) pada Kasus Hiv/Aids Di Jawa Timur
DOI:
https://doi.org/10.51402/jle.v2i1.7Keywords:
Generalized Additive Model for Location, Scale, and Shape (GAMLSS), Locally Estimated Scatterplot Smooting (LOESS), HIV/AIDSAbstract
HIV / AIDS is a contagious disease that can attack all age groups of the population and is a health challenge in almost all over the world including Indonesia. Therefore, it is necessary to model HIV / AIDS cases for the factors that are suspected to influence them. One suitable method for estimating factors that influence HIV / AIDS is the Generalized Additive Model for Location, Scale, and Shape (GAMLSS). The GAMLSS method is flexible because it includes expansion of a good exponential family distribution to handle overdispersion data, continuous data, and discrete data. This research will apply GAMLSS semiparametric modeling with LOESS smoothing to find out the characteristics and models of HIV / AIDS cases in East Java in 2017. Based on the analysis, it was found that the variables that significantly affected were the number of homeless people, number of victims of drug abuse, population poor, and the number of fertile age couples using condom contraception with AIC value of 437,404, degree = 1 and span = 0.3, and the distribution used is Negative Binomial I.
References
Akaike,H. 1978. A Bayesian Analysis of The Minimum AIC Prosedure. Annals of The Institute of Statistical Mathematics, Part A Hal.914. http://www.ism.ac.jp/editsec/aism/pdf/
Cleveland, W.S. 1979. Robust Locally Weighted Regression and Smoothing Scatterplots. Journal of The American Statistical Association, 74:829-836.
Cleveland W.S, Devlin,S.J. 1988. An Approach to Regression Analysis by Local Fitting. Journal of The American Statistical Association, 83:596-610.
Badan Pusat Statistik. 2018. Jawa Timur Dalam Angka. 2018. BPS Jawa Timur.Surabaya.
Departemen Kesehatan RI: Penanggulangan HIV/AIDS di Indonesia, Respon Saat ini Menangkal Ancaman Bencana Nasional AIDS Mendatang. Departemen Kesehatan RI. Jakarta: 2002.
Direktorat Jenderal Pencegahan dan Pengendalian Penyakit Kementerian Kesehatan RI: Laporan Perkembangan HIV/AIDS dan Penyakit Infeksi Menular Seksual Tahun 2016.
Fauziah, L. 2015. Aplikasi GAMLSS dengan Pemulusan Loess dan Algoritma Rigby-Stasinopoulos Pada Data Cacahan. Skripsi. Jember: Universitas Jember.
Hasanah, U. 2015. Aplikasi GAMLSS dalam Pemodelan Generalized Gamma dengan Algoritma Mixed pada Pemulusan Loess. Skripsi. Jember: Universitas Jember.
Hastie, T.J,Tibshirani,R.J.1990. Generalized Additive Models. Chapman and Hall: London.
Hardin, J. W., dan Hilbe, J. M. 2007. Generalized Linear Models and Extensions Second Edition. Texas: Stata Press.
Hilbe, J.M. 2011. Negative Binomial Regression Second Edition. New York: Cambridge University Press.
Herindrawati., dkk. 2017. Pemodelan Regresi Poisson Inverse Gaussian Studi Kasus : Jumlah Kasus Baru HIV di Provinsi Jawa Tengah Tahun 2015. Jurusan Statistika. Fakultas Matematika dan Ilmu Pengeta huan Alam, Institut Teknologi Sepuluh Nopember (ITS).
Jacoby, W.G. 2000. Loess : a nonparametric, graphical tool for depicting relationsips between variables. Electoral Studies.19:577-613.
Kemenkes RI. 2006. Profil Kesehatan Indonesia Tahun 2005. Jakarta: Kementerian Kesehatan Republik Indonesia.
Kemenkes RI. 2014. Profil Kesehatan Indonesia Tahun 2013. Jakarta: Kementerian Kesehatan Republik Indonesia.
Nelder, J.A.dan Wedderburn, R. W. M. 1972. Generalized Linear Models, J. R Statist. Soc. A.,135: 370-384
Pasokawati, Tsamara. 2019. Pemodelan Geographically Weighted Negative Binomial Regression Pada Kasus HIV di Jawa Timur. Skripsi. Semarang: Universitas Muhammadiyah Semarang.
Ramachandran, K. M dan Tsokos, C.P. 2009. Mathematical Statistic with Application. United States of America: Academic Press.
Rigby,R.A dan Stasinopoulos D.M.2005 Generalized Additive Models for Location, and Shape. Apllied Statistic,54.507-554
Rohimah, S., R. 2015. Model Spasial Autoregresif Poisson Untuk Mendeteksi Faktor-Faktor Yang Berpengaruh Terhadap Jumlah Penderita HIV Di Provinsi Jawa Timur. Program Studi Matematika, Jurusan Matematika, FMIPA, Universitas Negeri Semarang.
Stasinopoulos, D. M. & Rigby, R.A. 2007. Generalized Additive Models for Location, Scale and Shape (GAMLSS) in R. J.R.Statisc.
Stasinopoulos,D.M., Rigby,R.B.,Akantziliotou,C.2008. Instruction on How to Use The GAMLSS Package in R Second Edition. STORM Research Centre, London Metropolitan University, London. http://www.gamlss.com/
SAS Institute Inc. 1999. SAS Campus Drive, Cary, North Carolina 27513.
Tirta, IM. 2009. Analisis Regresi dengan R (ANRER). Jember: UPT Penerbitan Universitas Jember
Wahyuni, Rifka. 2016. Model Aditif Tergeneralisir Semiparametrik dengan Menggunakan Pemulusan Loess pada Kasus Pendugaan Curah Hujan. Skripsi. Jember: Universitas Jember.
World Health Organization. (2016). HIV and Young People Who Inject Drugs. Geneva: WHO Document Production Services.
