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%.
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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. Logistic regression |
| 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: | http://repository.its.ac.id/id/eprint/71821 |
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