Pemodelan Multivariate Adaptive Generalized Poisson Regression Spline (MAGPRS) pada Kasus Jumlah Penyakit Tuberkulosis di Provinsi Sumatera Utara

Setiawan, Ezra Alfonsius (2023) Pemodelan Multivariate Adaptive Generalized Poisson Regression Spline (MAGPRS) pada Kasus Jumlah Penyakit Tuberkulosis di Provinsi Sumatera Utara. Other thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Tuberkulosis merupakan penyakit infeksi menular yang disebabkan oleh infeksi bakteri berbentuk batang, Mycobacterium tuberculosis. Dari laporan yang dikeluarkan oleh WHO tentang tuberkulosis secara global, Indonesia menjadi negara dengan jumlah kasus terbanyak kedua di dunia. Sumatera Utara merupakan salah satu provinsi dengan jumlah kasus tuberkulosis yang cukup banyak di Indonesia dengan jumlah kasus 22.169. Salah satu upaya yang dapat dilakukan dalam rangka pencegahan tuberkulosis di Sumatera Utara adalah melakukan pemodelan jumlah kasus tuberkulosis menggunakan metode Multivariate Adaptive Generalized Poisson Regression Spline (MAGPRS). Pemodelan dilakukan menggunakan kombinasi Basis Fungsi (BF) berjumlah 20, 30, dan 40; Maksimum Interaksi (MI) berjumlah 1, 2, dan 3; dan Minimum Observasi (MO) berjumlah 0, 1, 2, dan 3. Model terbaik dari hasil analisis MAGPRS adalah model dengan jumlah BF=30, MI=2, dan MO=3. Setelah dilakukan backward stepwise, diperoleh jumlah basis fungsi optimum sejumlah 26. Variabel prediktor yang paling berpengaruh terhadap model secara berurutan adalah variabel jumlah rumah sakit umum, persentase perokok, serta persentase desa/kelurahan yang memiliki rumah sakit.
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Tuberculosis is a contagious infectious disease caused by a rod-shaped bacterial infection, Mycobacterium tuberculosis. From a report issued by WHO on tuberculosis globally, Indonesia is the country with the second highest number of cases in the world. North Sumatra is one of the provinces with a large number of tuberculosis cases in Indonesia with a total of 22,169 cases. One of the efforts that can be made to prevent tuberculosis in North Sumatra is to model the number of tuberculosis cases using the Multivariate Adaptive Generalized Poisson Regression Spline (MAGPRS) method. The best model from the results of the MAGPRS analysis is the model with BF=30, MI=2, and MO=3. After doing backward stepwise, the optimal number of functional basis is obtained as many as 26. The predictor variables that have the most influence on the model sequentially are the number of public hospitals, the percentage of smokers, and the percentage of villages that have hospitals.

Item Type:	Thesis (Other)
Uncontrolled Keywords:	MAGPRS, Pola Data, Poisson, Sumatera Utara, Tuberkulosis, Data Pattern, MAGPRS, North Sumatra, Poisson, Tuberculosis
Subjects:	H Social Sciences > HA Statistics > HA30.6 Spatial analysis H Social Sciences > HA Statistics > HA31.3 Regression. Correlation Q Science > QA Mathematics > QA278.2 Regression Analysis. Logistic regression
Divisions:	Faculty of Science and Data Analytics (SCIENTICS) > Statistics > 49201-(S1) Undergraduate Thesis
Depositing User:	Ezra Alfonsius Setiawan
Date Deposited:	10 Aug 2023 06:43
Last Modified:	10 Aug 2023 06:43
URI:	http://repository.its.ac.id/id/eprint/104473

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