Analisis Path Nonparametrik Variabel Laten: Pendugaan Fungsi Dan Pengujian Hipotesis

Hidayat, Muhamad Fariq (2020) Analisis Path Nonparametrik Variabel Laten: Pendugaan Fungsi Dan Pengujian Hipotesis. Magister thesis, Universitas Brawijaya.

Abstract

Penelitian ini untuk mengidentifikasi pola hubungan antar variabel manifest dan variabel laten. Analisis path parametrik merupakan salah satu teknik analisis yang tepat digunakan untuk bentuk kurva diketahui. Fenomena menyatakan sulit untuk mendapat bentuk kurva atau bentuk kurva tidak diketahui. Analisis path nonparametrik digunakan untuk menduga fungsi dengan pendekatan truncated spline yang berisi parameter derajat polinomial dan titik knot. Kasus teknik revegetasi lahan pascatambang digunakan sebagai studi kasus karena pola hubunga antara variabel tidak linier. PCA dilakukan untuk mengukur indikator masing-masing variabel, guna kontribusi komponen variabel serta variabel yang digunakan tercermin oleh indikator terkuat dan mengandung sebagian informasi diukur dalam keragaman total yang hanya ada pada beberapa PC saja. Hasil penelitian didapatkan bahwa model terbaik analisis path dengan derajat polinomial linier dan titik knot 3 dengan nilai GCV 1738,303. Variabel Umur revegetasi berpengaruh terhadap Diversitas Vegetasi atau pada path hubungan antara variabel X1 terhadap Y1 ditandai dengan nilai p-value sebesar 0,001.

English Abstract

This study is to identify patterns of relationships between manifest variables and latent variables. Parametric path analysis is one of the appropriate analytical techniques used to form unknown curves. The phenomenon proofs that it is difficult to get a curve shape or curve shape is unknown. Nonparametric path analysis is used to estimate the function with the truncated spline approach that contains parameters polynomial degrees and knots. The case of the post-mining revegetation technique is used because the researcher found that there is a pattern of relationships between variables is not linear. Principle Component Analysis (PCA) is carried out to measure the indicators of each variable so that the contribution of component variables and variables used is reflected by the strongest indicators also contains some of the information measured in total diversity that only exists in a few component. The results showed that the best model of path analysis with linear polynomial degrees and knot point 3 with a GCV value of 1738,303. The age of revegetation variable influences vegetation diversity or the path of the relationship between variables X1 to Y1 is marked by a p-value of 0.001.

Other obstract

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Item Type:	Thesis (Magister)
Identification Number:	0420090013
Uncontrolled Keywords:	Analisis Path, PCA, GCV, Truncated spline, polynomial, knot, Nonparametrik, Lahan pascatambang.
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 > 519.537 Correlation analysis (Association analysis)
Divisions:	Fakultas Matematika dan Ilmu Pengetahuan Alam > Statistika
Depositing User:	ismanto
Date Deposited:	25 Feb 2021 14:33
Last Modified:	20 Sep 2024 02:31
URI:	http://repository.ub.ac.id/id/eprint/183690

Text tesis- muhamad fariq hidayat - s2 stat - MUHAMAD FARIQ HIDAYAT.pdf Download (15MB)

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