Rahmansyah, Melati Sukma Ayu (2020) Pemodelan Multivariate Adaptive Regression Spline (Mars) Biner Untuk Klasifikasi Penyakit Hepatitis B Pada Ibu Hamil Di Kota Malang Tahun 2018. Sarjana thesis, Universitas Brawijaya.
Abstract
Multivariate Adaptive Regression Spline (MARS) merupakan suatu metode analisis yang digunakan untuk memodelkan regresi nonparametrik multivariat antara variabel respon dan beberapa variabel prediktor. Model MARS berguna untuk mengatasi permasalahan data berdimensi tinggi dan menghasilkan prediksi variabel respon yang akurat serta menghasilkan model kontinu dalam knot berdasarkan nilai GCV terkecil. Penelitian ini menggunakan variabel respon biner tentang status Hepatitis B pada ibu hamil serta umur
English Abstract
Multivariate Adaptive Regression Spline (MARS) is an analytical method used to model multivariate nonparametric regression between response variables and several predictor variables. The MARS model is useful for overcoming problems of high-dimensional data and producing accurate prediction of response variables as well as producing continuous models in knots based on the smallest GCV value. This study uses binary response variables on the status of Hepatitis B in pregnant women and age
Other obstract
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| Item Type: | Thesis (Sarjana) |
|---|---|
| Identification Number: | 0520090121 |
| Uncontrolled Keywords: | Hepatitis B, MARS, Tingkat Ketepatan Klasifikasi, Uji Press’s Q. |
| Subjects: | 500 Natural sciences and mathematics > 519 Probabilities and applied mathematics > 519.5 Statistical mathematics > 519.53 Descriptive statistics, multivariate analysis, analysis of variance and covariance > 519.536 Regression analysis |
| Divisions: | Fakultas Matematika dan Ilmu Pengetahuan Alam > Statistika |
| Depositing User: | ismanto |
| Date Deposited: | 10 Feb 2021 09:06 |
| Last Modified: | 20 Jul 2022 02:42 |
| URI: | http://repository.ub.ac.id/id/eprint/182630 |
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