Penanganan Multikolinearitas pada Model Pembentuk Indeks Pembangunan Manusia Provinsi Jawa Timur Menggunakan Principal Component Regression

Nariswari, Naura Dahayu Dhia and Iswara, Widya (2024) Penanganan Multikolinearitas pada Model Pembentuk Indeks Pembangunan Manusia Provinsi Jawa Timur Menggunakan Principal Component Regression. Project Report. [s.n.], [s.l.]. (Unpublished)

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Abstract

Indeks Pembangunan Manusia (IPM) menunjukkan kualitas hidup manusia yang meliputi aspek harapan hidup, pendidikan, dan standar hidup layak. Penelitian ini bertujuan untuk memodelkan faktor-faktor yang memengaruhi IPM masing-masing daerah di Provinsi Jawa Timur menggunakan Principal Component Regression (PCR). Data yang digunakan adalah data sekunder dari Badan Pusat Statistika (BPS) yang diduga merupakan faktor yang memengaruhi IPM. Penelitian ini dimulai dengan menganalisis statistika deskriptif, membentuk model regresi linier berganda, membentuk model Principal Component Analysis, dan membentuk model Principal Component Regression. Dari hasil analisis diperoleh model PCR dengan nilai adjusted R Square sebesar 0,904 sehingga model regresi dikatakan sangat baik karena dapat menjelaskan sekitar 90,4% dari variabilitas total dalam data respon menggunakan principal component yang dipilih dalam model.
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The Human Development Index (HDI) shows the quality of human life which includes aspects of life expectancy, education, and decent living standards. This study aims to model the factors that influence HDI of each region in East Java Province using Principal Component Regression (PCR). The data used is secondary data from the Central Bureau of Statistics (BPS) which is thought to be a factor that affects HDI. This research begins by analyzing descriptive statistics, forming multiple linear regression models, forming Principal Component Analysis models, and forming Principal Component Regression models. From the analysis, the PCR model is obtained with an adjusted R Square value of 0.904 so that the regression model is said to be very good because it can explain about 90.4% of the total variability in the response data using the principal component selected in the model.

Item Type:	Monograph (Project Report)
Uncontrolled Keywords:	The Human Development Index, East Java, Regression, Principal Component Analysis, Principal Component Regression, Analisis Komponen Utama Index Pembangunan Manusia, Jawa Timur, Regresi, Regresi Komponen Utama
Subjects:	Q Science > QA Mathematics > QA278.2 Regression Analysis. Logistic regression Q Science > QA Mathematics > QA278.5 Principal components analysis. Factor analysis. Correspondence analysis (Statistics)
Divisions:	Faculty of Mathematics, Computation, and Data Science > Actuaria > 94203-(S1) Undergraduate Thesis
Depositing User:	Widya Iswara
Date Deposited:	07 Jan 2025 04:26
Last Modified:	07 Jan 2025 04:26
URI:	http://repository.its.ac.id/id/eprint/116201

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