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All Journal RADIAL: JuRnal PerADaban SaIns RekAyasan dan TeknoLogi MURHUM : JURNAL PENDIDIKAN ANAK USIA DINI Multidiciplinary Output Research for Actual and International Issue (Morfai Journal) Jurnal Pengabdian Masyarakat : Pemberdayaan, Inovasi dan Perubahan Jurnal Ilmiah Kesehatan Masyarakat Jurnal Pemberdayaan: Publikasi Hasil Pengabdian kepada Masyarakat (JPM ITTC ) Open Community Service Journal Journal of Food and Agricultural Product Asian Journal of Science Education RADIAL: Jurnal Peradaban Sains, Rekayasa dan Teknologi Integra: Journal of Integrated Mathematics and Computer Science
Lestari, Windi
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Journal : Integra: Journal of Integrated Mathematics and Computer Science

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Robust Panel Data Regression Analysis using the Least Trimmed Squares (LTS) Estimator on Poverty Line Data in Lampung Province Lestari, Windi; Widiarti; Utami, Bernadhita Herindri Samodera; Usman, Mustofa; Handayani, Vitri Aprilla
Integra: Journal of Integrated Mathematics and Computer Science Vol. 1 No. 2 (2024): July
Publisher : Magister Program of Mathematics, Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26554/integrajimcs.20241210

Abstract

Robust regression is an alternative method in regression analysis designed to produce stable parameter estimates, even when the data contain outliers or deviate from classical assumptions. One of its estimation techniques, the Least Trimmed Square (LTS),works by minimizing the smallest squared residuals, thereby assigning smaller weights to extreme data points. This method serves as a solution when classical approaches, such as Ordinary Least Squares (OLS), fail to meet the assumptions, especially in socio-economic data that are often complex and prone to outliers. This study employs robust regression with the LTS estimator on panel data to examine the impact of population size , population density , and registered job vacancies on poverty lines in Lampung Province. The data cover 15 districts and cities from 2019 to 2023. The analysis results show that the model obtained has a coefficient of determination of R2=0.8909. This means that the three predictor variables can explain 89.09% of the variation in the poverty line.
Co-Authors ., Nasywa Aldoni, M. Asroh, Ardi Citra Pratiwi Prayitno Defira, Citra Desva, Rayhan Azky Ekawati Danial Endang Lastinawati, Endang Fatmanurshanti, Dora Febriana, Khairi Hayad Fetris, Shatzi Laura Gribaldi Gribaldi Hafidz, Muhammad Al Handayani, Vitri Aprilla Ichsan, Onne Akbar Nur Kasli, Elisa Kasmuddin, Kasmuddin Mahani, Bila Muhammad Irfan Nasution Mustofa Usman Novriani, Novriani Nurlaili Nurlaili Nurmala Dewi, Nurmala Purwadi Purwadi Pusvita, Ema Putri Ayu Ogari, Putri Ayu Putri, Piranti Herdaning Rantisari T, A. Meinar Dwi Rosmawati, Henny Safitri, Margeliza Sakalena, Firnawati Saleh, Adriandy Saputra, Doris Sastra, Ryandra Septianita, Septianita Sujatmiko, Harumi Susanti - Diana Tumampas, Kevien Glendi Usman Usman Utami, Bernadhita Herindri Samodera Widiarti Yulhasmir, Yulhasmir Yulianti Rasyid Yusrizal Yusrizal Zulhidayah, Tri