BOOSTED REGRESSION TREES

Wulan Dian Pramiesti, - (2020) BOOSTED REGRESSION TREES. S1 thesis, Universitas Pendidikan Indonesia.

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Official URL: http://repository.upi.edu

Abstract

Pohon regresi merupakan teknik analisis data yang bertujuan untuk mengetahui pengaruh semua peubah penjelas terhadap peubah responnya. Namun, ternyata metode pohon regresi memiliki kelemahan yaitu struktur hierarkisnya memungkinkan terjadinya varians yang tinggi. Kelemahan metode pohon regresi ini dapat diatas dengan menggunakan pendekatan Boosted Regression Trees (BRT). Pendekatan BRT menggunakkan teknik boosting untuk menggabungkan beberapa pohon regresi secara aditif sehingga varians yang dihasilkan menurun dari sebelumnya. Penelitian ini menggunakan metode BRT untuk studi kasus faktor-faktor yang memengaruhi tingkat kriminalitas di Jawa Timur tahun 2018. Hasil penelitian menunjukkan turunnya nilai error dan pohon optimal yang harus terbentuk 89 pohon. Faktor yang memengaruhi tingkat kriminalitas tertinggi adalah jumlah pemuda (31,86%), diikuti oleh persentase penduduk miskin (11,14%), APK SMP (9,67%), APK SD (8,98%), kemantapan jalan (8.81%), APK SMA (8,67%), jarak ke ibukota surabaya (7,25%), tingkat pengangguran terbuka (7,02%), PDRB (5,32%), dan kepadatan penduduk (1,25%). A regression tree is a data analysis technique that aims to determine the effect of all explanatory variables on the response variables. However, it turns out the regression tree method has a weakness that is the hierarchical structure allows for high variance predictors. The weakness of this regression tree method can be above using the Boosted Regression Trees (BRT) approach. The BRT approach uses additive boosting techniques to combine multiple regression trees so that the resulting variance decreases from before. This study uses the BRT method for a case study of factors affecting the level of crime in East Java in 2018. The results showed a decrease in the error value and the optimal tree that had to be formed by 89 trees. The most important crime rate factors are the number of youth (model importance of 31.86%), followed by the percentage of poor population (11.14%), junior high school gross enrollment rate (9.67%), elementary school gross enrollment rate (8.98%), road stability (8.81 %), senior high school gross enrollment rate (8.67%), distance to the capital city of Surabaya (7.25%), open unemployment rate (7.02%), Gross Domestic Regional Product (GRDP) (5.32%), and population density (1.25%).

Item Type: Thesis (S1)
Uncontrolled Keywords: pohon regresi, boosting, boosted regression trees, tingkat kriminalitas
Subjects: L Education > L Education (General)
Q Science > QA Mathematics
Divisions: Fakultas Pendidikan Matematika dan Ilmu Pengetahuan Alam > Jurusan Pendidikan Matematika > Program Studi Matematika (non kependidikan)
Depositing User: Wulan Dian Pramiesti
Date Deposited: 18 Feb 2020 02:23
Last Modified: 18 Feb 2020 02:23
URI: http://repository.upi.edu/id/eprint/46865

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