Pemodelan Faktor-Faktor Yang Memengaruhi Angka Morbiditas Di Provinsi Jawa Tengah Menggunakan Regresi Nonparametrik Spline Truncated

Rosanti, Irma Wahyu (2020) Pemodelan Faktor-Faktor Yang Memengaruhi Angka Morbiditas Di Provinsi Jawa Tengah Menggunakan Regresi Nonparametrik Spline Truncated. Undergraduate thesis, Institut Teknologi Sepuluh Nopember.

[thumbnail of 06211640000002-Undergraduate_Thesis.pdf]
Preview
Text
06211640000002-Undergraduate_Thesis.pdf

Download (2MB) | Preview

Abstract

Morbiditas merupakan angka yang menggambarkan banyaknya penyakit atau keluhan kesehatan dalam suatu populasi pada kurun waktu tertentu. Morbiditas menjadi salah satu indikator yang digunakan untuk mengukur tingkat kesehatan masyarakat. Semakin tinggi morbiditas maka semakin banyak penduduk yang mengalami keluhan kesehatan dan derajat kesehatan masyarakat semakin buruk. Pada tahun 2018 morbiditas di Jawa Tengah mencapai 15,15%. Angka morbiditas tersebut tertinggi di Pulau Jawa dan di atas rata-rata morbiditas nasional yang hanya mencapai 13,91%. Penelitian ini dilakukan untuk mengetahui faktor-faktor yang diduga mempengaruhi morbiditas di Jawa Tengah menggunakan Regresi Nonparametrik Spline Truncated. Metode ini digunakan karena pola hubungan antara morbiditas dan faktor-faktor yang diduga berpengaruh tidak mengikuti pola data tertentu. Hasil penelitian menunjukkan bahwa model regresi nonparametrik spline terbaik adalah menggunakan kombinasi knot 2,3,2,3,3,3 dan seluruh variabel yang digunakan dalam penelitian berpengaruh signifikan terhadap morbiditas di Jawa Tengah. Variabel yang digunakan yaitu kepadatan penduduk, persentase penduduk miskin, rata-rata lama sekolah, Upah Minimum Kabupaten/Kota, persentase rumah tangga ber-PHBS, dan persentase penduduk dengan akses sanitasi layak. Koefisien determinasi dari model sebesar 98,45%.
==================================================================================================
Morbidity is a number that describes the amount of disease or health complaints in a population at a certain time. Morbidity is one indicator used to measure the level of public health. If morbidity increases, the number of people have experience with health complaints increases and the degree of public health gets worse. In 2018, the morbidity in Central Java reached 15.15%. This result is the highest morbidity rate in Java and above the national average morbidity, which only reaches 13.91%. This study was conducted to determine the factors that are influence morbidity in Central Java using Nonparametric Spline Truncated Regression. This method was used because the relationship pattern between morbidity and factors influential does not follow the data patterns. The results show that the best nonparametric spline regression model is to use a combination of knots 2,3,2,3,3,3. All variables used in the study have a significant effect on morbidity in Central Java. The variables used are population density, poor population percentage, the length average of schooling, Regency/City Minimum Wage, the percentage of households with PHBS, and the percentage of population with access to proper sanitation. The coefficient of determination of the model is 98.45%.

Item Type: Thesis (Undergraduate)
Additional Information: RSSt 519.536 Ros p-1 • Rosanti, Irma Wahyu
Uncontrolled Keywords: Central Java, GCV, Knot Points, Morbidity, Nonparametric Regression, Spline Truncated, Jawa Tengah,GCV, Titik Knot, Morbiditas, Regresi Nonparametrik, Spline Truncated
Subjects: H Social Sciences > HA Statistics
H Social Sciences > HA Statistics > HA29 Theory and method of social science statistics
H Social Sciences > HA Statistics > HA31.35 Analysis of variance
H Social Sciences > HA Statistics > HA31.3 Regression. Correlation
H Social Sciences > HA Statistics > HA31.7 Estimation
H Social Sciences > HN Social history and conditions. Social problems. Social reform
Q Science > QA Mathematics > QA278.2 Regression Analysis. Logistic regression
R Medicine > RA Public aspects of medicine > RA0421 Public health. Hygiene. Preventive Medicine
Divisions: Faculty of Mathematics and Science > Statistics > 49201-(S1) Undergraduate Thesis
Depositing User: Irma Wahyu Rosanti
Date Deposited: 26 Aug 2020 02:48
Last Modified: 21 May 2023 16:08
URI: http://repository.its.ac.id/id/eprint/81210

Actions (login required)

View Item View Item