Pemodelan Jumlah Penderita Campak Di Indonesia Dengan Pendekatan Regresi Nonparametrik Spline - The Modelling Of Measles Patients Number In Indonesia By Using Nonparametric Spline Regression Approach

Nawaafila, . (2015) Pemodelan Jumlah Penderita Campak Di Indonesia Dengan Pendekatan Regresi Nonparametrik Spline - The Modelling Of Measles Patients Number In Indonesia By Using Nonparametric Spline Regression Approach. Undergraduate thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Campak merupakan salah satu penyakit penyebab kematian di Indonesia. Pada tahun 2013, lebih dari 70 persen kematian di dunia disebabkan karena campak. Jumlah kasus penderita campak di Indonesia tahun 2013 yaitu sebanyak 4.300.824 kasus. Campak di Indonesia masih tergolong tinggi meskipun pemerintah sudah menerapkan imunisasi campak, hal ini disebabkan pelayanan di Indonesia masih menitikberatkan pada pelayanan kuratif dan rehabilitatif, sehingga permasalahan campak ini sangat kompleks dan krusial. Untuk itu perlu adanya pencegahan, salah satunya dengan mengetahui faktor-faktor yang berpengaruh terhadap jumlah kasus penderita campak di Indonesia. Tujuan penelitian ini adalah untuk mengetahui faktor-faktor yang berpengaruh terhadap jumlah kasus penderita campak dengan menggunakan metode Regresi Nonparametrik Spline. Dalam penelitian ini Scatterplot antara variabel respon dengan variabel prediktor tidak membentuk pola tertentu, sehingga metode yang digunakan adalah regresi nonprametrik spline dengan pemilihan titik knot optimum berdasarkan nilai Generalized Cross Validation (GCV) terkecil. Berdasarkan hasil analisis model terbaik adalah kombinasi knot 2,2,3 dengan variabel yang signifikan terhadap model regresi nonparametrik spline adalah persentase balita kekurangan gizi (x3), kepadatan penduduk (x4), dan jumlah tenaga sanitasi (x5). Model regresi nonparametrik spline yang terbentuk menghasilkan nilai koefisien determinasi sebesar 97,82%. ======================================================================================================================== Measles is one of deathly diseases in Indonesia. In 2013, more than 70% death in the world is caused by measles. The numbers of measles patients in Indonesia in 2013 are 4.300.824 cases. Measles in Indonesia is highly rated even though government has applied measles imunitation. This condition is affected by the fact that Indonesia is still concerned on its curativ and rehabilitative services so that such problem is complex and crucial. Based on that fact, preventations will be created in which one of the ways is by finding the relevant factors towards the numbers of measles patients in Indonesia. One of methods which is used to find out the relationship among variables is by using regression analysis. The purpose of this observation was to determine the factors that influence the number of cases of measles by using Nonparametric Spline Regression. In this observation, Scatterplot between respond and predictor variable do not form particular pattern, therefore the method used is Nonparametic Spline Regression by selecting the optimum knot period which is based on the smallest values of Generalized Cross Validation (GCV). Based on the analysis result, the best model is knot combination of 2,2,3 in which the significant variable towards nonparametic spline regression model are the percentage of malnutrision infant (x3), population density (x4), and sanitation power (x5). Nonparametic spline regression model formed results the determination of coofeciency value by 97,82%.

Item Type: Thesis (Undergraduate)
Additional Information: RSSt 519.536 Naw p
Uncontrolled Keywords: Generalized Cross Validation (GCV), Jumlah Penderita Campak, Titik Knot Optimum, Regresi Nonparamerik Spline, Generalized Cross Validation (GCV), Measles Patients Number, Knot Optimum Period, Nonparametric Spline Regression
Subjects: Q Science > QA Mathematics > QA278.2 Regression Analysis
Divisions: Faculty of Mathematics and Science > Statistics
Depositing User: ansi aflacha
Date Deposited: 15 Nov 2019 04:21
Last Modified: 15 Nov 2019 04:21
URI: https://repository.its.ac.id/id/eprint/71821

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