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All Journal Indonesian Journal of Artificial Intelligence and Data Mining Jurnal Ilmiah Ilmu Komputer Fakultas Ilmu Komputer Universitas Al Asyariah Mandar Pelita Eksakta ILKOMNIKA: Journal of Computer Science and Applied Informatics GAUSS: Jurnal Pendidikan Matematika Suluah Bendang: Jurnal Ilmiah Pengabdian Kepada Masyarakat Rangkiang Mathematics Journal UNP Journal of Statistics and Data Science Mathematical Journal of Modelling and Forecasting Indonesian Journal of Statistics and Its Applications
Zilrahmi, Zilrahmi
Department Of Statistics, Universitas Negeri Padang
Humanities Biochemistry, Genetics & Molecular Biology Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Mathematics Physics Social Sciences Other

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Journal : mathematical journal of modelling and forecasting

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Application of Principal Component Analysis in Identifying Factors Affecting the Human Development Index Faisal, Muhammad; Fitri, Fadhilah; Zilrahmi
Mathematical Journal of Modelling and Forecasting Vol. 2 No. 2 (2024): December 2024
Publisher : Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/mjmf.v2i2.26

Abstract

This study examines the Human Development Index (HDI) in West Sumatra Province in 2023. The HDI is an essential indicator for measuring the success of efforts to improve the quality of human life. This research aims to identify the key factors that influence the HDI. The HDI is constructed from three fundamental dimensions that indicate human quality of life: health, education, and economy. The factors within each dimension tend to be strongly correlated, as they mutually influence one another, potentially leading to multicollinearity issues. Therefore, an analysis is conducted to reduce the number of original variables into new orthogonal variables while preserving the total variance of the original variables using Principal Component Analysis (PCA). Based on this background, the study applies PCA to address multicollinearity and to identify new, more representative variables. The study findings indicate that the factors influencing the HDI are the education and economic and health welfare indexes.
Co-Authors Abilya Amanda Adinda Dwi Putri Afifa Lufti Insani Amelia Fadila Rahman Atus Amadi Putra Chairina Wirdiastuti Devi Yopita Sipayung Dila Sari Dina Fitria Dina Fitria Dina Fitria Dina Fitria, Dina Dinda Fitriza Diva Aliyah Dodi Vionanda Dodi Vionanda Dony Permana Dony Permana Dwi Sulistiowati Fadhilah Fitri Fadhilah Fitri Fadhilah Fitri Fadhillah Fitri Fadhira Vitasha Putri Fajri Juli Rahman Nur Zendrato Fajrin Putra Hanifi Farit M Afendi FAZHIRA ANISHA Febri Ramayanti Fedisha Elfiri Fedisha Fitri Mudia Sari Fitri, Fadhilah Frandito Rahmanesta Gilang Ibnul farizi Hadid Habiburrahman Hamida, Zilfa Hanifah Nazhiroh Hari Wijayanto Ichlas Djuazva Ihsanul Fikri Khoirun Nisa Lathifa Putri Listia Maharani M. Anfasa Prana Karil Manja Danova Putri Martia Rosada Meliani Maya Sari Meliani Putri Melin Wanike Ketrin Mellisa Ayuningtyas Moh. Erkamim Muhammad Alif Yustin Muhammad Fadhil Aditya Aditya Muhammad Fadlan Rafly Muhammad Faisal Muhammad Hendrawan Muslimah, Nailul Amani Mutiara Amazona Sosiawati Naila Marettania Nilda Yanti Nonong Amalita Nurdalia Nurviqotun Khasanah Nurwijayanti Permana, Dony Rahmad Wanizal Pastha Rahmadani Iswat Retno Lis Megawati Rita Diana Rizal Bakri Rizqa Fajriaty Fitri MY Said Thaufik Rizaldi Salma, Admi Sepriano Sepriano silfia wisa fitri Sindy Amelia Putri Sri Wahyu suci Sulhatun Sulhatun Syafriandi Syafriandi Syafriandi Syafriandi Syafriandi Syafriandi Syifa Azahra Syifa Miftahurrahmi Syifa Nabilah Wandira Tessy Octavia Mukhti Tessy Octavia Mukhti Ully Martha martha Ulya Syafitri.J Vania Riski Afifah Velya Rahma Putri Widia Handa Riska Winalia Agwil Yarman Yarman, Yarman Yenni Kurniawati Yenni Kurniawati Yurivo Rianda Saputra Zamahsary Martha Zamahsary Martha