Identifikasi Distribusi dan Pendugaan Parameter Jumlah Kematian Bayi di Kabupaten Padang Pariaman dengan Menggunakan Metode Bayes
DOI:
https://doi.org/10.25077/jmua.11.4.220-229.2022Keywords:
Distribusi Poisson, Jumlah Kematian Bayi, Metode Bayes, Posterior GammaAbstract
Kematian bayi adalah kematian yang terjadi antara saat setelah bayi lahir sampai bayi belum berusia tepat satu tahun. Angka Kematian Bayi (AKB) adalah banyaknya kematian bayi berusia di bawah satu tahun per 1.000 kelahiran hidup pada satu tahun tertentu. Rata-rata jumlah kematian bayi perlu diketahui sebagai upaya untuk mengurangi angka kematian bayi. Pada penelitian ini akan diduga rata-rata kematian bayi tiap puskesmas di Kabupaten Padang Pariaman menggunakan metode Bayes. Data yang digunakan adalah data jumlah kematian bayi di puskesmas di Kabupaten Padang Pariaman sepanjang tahun 2019 dan 2020. Telah diperlihatkan bahwa jumlah kematian bayi menyebar menurut sebaran Poisson. Sebaran prior yang digunakan adalah sebaran Gamma, Uniform dan dengan metode Jeffrey. Rata-Rata jumlah kematian bayi diduga dari sebaran posterior Gamma, diperoleh dugaan rata-rata kematian bayi adalah sebesar 0, 83 per puskesmas. Disimpulkan juga bahwa pendugaan Bayes dengan distribusi prior Gamma lebih baik dibandingkan distribusi prior lainnya.Downloads
References
Bain, L.J and M. Engelhardt. 1992. Introduction to Probability and
Mathematical Statistics Second Edition. Duxbury Press, California.
Box, G.E.P and G.C. Tiao. 1973. Bayesian Inference in Statistical
Analysis. Addison-Wesley Publishing Company, Inc. Philipines.
Yanuar, F. 2019. Statistika Bayesian. CV. IRDH, Yogyakarta.
Hajarisman, dkk. 2013. Pendugaan Angka Kematian Bayi Melalui Model Poisson Bayes Berhirarki Dua-Level. Artikel Statistika. Vol.13(2): 81-92
Hasanah, U. 2018. Pendugaan Parameter dari Distribusi Gamma dengan
Metode Bayes. Skripsi S1, tidak diterbitkan. Fakultas Matematika dan Ilmu
Pengetahuan Alam Universitas Andalas. Padang.
Kementrian Kesehatan. 2014. Profil Kesehatan 2014 Dinas Kesehatan Provinsi
Sumatera Barat. https://pusdatin.kemenkes.go.id, tanggal akses 22 April 2022.
Rahmadiah, A. 2018. Inferensia Bayesian pada Distribusi Eksponensial. Skripsi
S1, tidak diterbitkan. Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Andalas. Padang.
Siegel, S. 1985. Statistik Nonparametrik. PT Gramedia, Jakarta.
Speigel, M.R, J.J. Schiller and R.A. Srinivasan. 2009. Probability and Statistics
Third Edition. The McGraw-Hill Companies Inc., New York.
Speigel, M.R, J.J. Schiller and R.A. Srinivasan. 2009. Probability and Statistics
Third Edition. The McGraw-Hill Companies Inc., New York.
Walpole, R.E and R.H. Myers. 1995. Probability and Statistics for Engineers
Scientists Nine Edition. Pearson Education Inc, New of America.
Walpole, R.E. 1993. Pengantar Statistika Edisi Ketiga. PT Gramedia, Jakarta.
Downloads
Additional Files
Published
How to Cite
Issue
Section
License
All articles published in Jurnal Matematika UNAND (JMUA) are open access and licensed under the Creative Commons Attribution-ShareAlike 4.0 International License (CC BY-SA 4.0). This license allows published content to be freely accessed, shared, redistributed, and adapted for any purpose, including commercial use, provided that the applicable license conditions are followed.
Copyright Holder
The copyright of articles published in Jurnal Matematika UNAND is held by the Departemen Matematika dan Sains Data, Fakultas Matematika dan Ilmu Pengetahuan Alam (FMIPA), Universitas Andalas (UNAND), in accordance with the journal's stated copyright policy.
Author Rights
Under the CC BY-SA 4.0 license, authors may share, distribute, and reuse their published articles, subject to the applicable license conditions. These rights include:
-
Self-Archiving: Authors may deposit their published articles in institutional repositories, personal websites, or academic platforms.
-
Reuse: Authors may reuse their published work in subsequent publications, research, teaching materials, or other lawful purposes, provided that appropriate attribution is maintained.
-
Distribution: Authors may share and distribute their published articles without requiring additional permission under the terms of the license.
Creative Commons License (CC BY-SA 4.0)
Under the CC BY-SA 4.0 license, users are free to:
-
Share: Copy and redistribute the material in any medium or format.
-
Adapt: Remix, transform, and build upon the material for any purpose, including commercial purposes.
These permissions are subject to the following conditions:
-
Attribution: Users must give appropriate credit to the original author(s), retain relevant copyright notices, provide a link to the license, and indicate if changes were made. Attribution must not imply endorsement by the author(s), copyright holder, or journal.
-
ShareAlike: If users remix, transform, or build upon the material, they must distribute their contributions under the same CC BY-SA 4.0 license or a compatible license.
-
No Additional Restrictions: Users may not apply legal terms or technological measures that legally restrict others from exercising the rights granted by the license.
For more information about the CC BY-SA 4.0 license, please visit:
https://creativecommons.org/licenses/by-sa/4.0/
Third-Party Content
Third-party materials, including figures, tables, photographs, and illustrations, are covered by the article's CC BY-SA 4.0 license only when their inclusion under that license is authorized.
Materials excluded from the license must be clearly identified with appropriate copyright notices and attribution. Authors are responsible for obtaining any necessary permissions, while users must comply with the applicable licensing terms or permissions when reusing excluded materials.
Copyright and Licensing Information
Copyright and licensing information should be clearly displayed on each published article's landing page and included in the full-text versions (HTML and PDF), where applicable, to ensure transparency regarding copyright ownership and permitted reuse.
