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All Journal Epsilon: Jurnal Matematika Murni dan Terapan Jurnal Matematika Sains dan Teknologi BAREKENG: Jurnal Ilmu Matematika dan Terapan Jurnal Pengabdian Sumber Daya Manusia Jurnal Pengabdian Pada Masyarakat OMNICODE Journal (Omnicompetence Community Developement Journal) RAGAM: Journal of Statistics and Its Application
Lestia, Aprida Siska
Program Studi Matematika FMIPA Universitas Lambung Mangkurat
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Journal : RAGAM: Journal of Statistics and Its Application

 1 
ESTIMASI PARAMETER RANDOM EFFECT MODEL PADA REGRESI PANEL MENGGUNAKAN METODE GENERALIZED LEAST SQUARE (STUDI KASUS: KEMISKINAN DI PROVINSI KALIMANTAN SELATAN) Ariandy Hermawan; Yuana Sukmawaty; Aprida Siska Lestia
RAGAM: Journal of Statistics & Its Application Vol 1, No 1 (2022): RAGAM: Journal of Statistics and Its Application
Publisher : Universitas Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/ragam.v1i1.7419

Abstract

Poverty is a condition that concerns the inability to meet the most minimum demands of life, especially from the aspects of consumption, income, education, and health. The problem of poverty is very complex and multidimensional in nature, as it relates to social, economic, cultural and other aspects. This study focuses on observation areas in South Kalimantan Province, with the PPM value in 2021 reaching (4.83%) still above the target goal of the Regional Medium-Term Development Plan (RPJMD) of South Kalimantan Province (3.96- 4.01%), so that further interventions are still needed to be able to reduce PPM in poverty cases. This study aims to estimate the parameters of the panel regression model used to analyze factors that are suspected to affect poverty cases in South Kalimantan Province in 2016-2020. The Random Effect Model (REM) is the best model used in this study, assuming that there are differences in slopes and interceptions caused by residual due to differences between individual units and between time periods. The process of estimating parameters on REM is determined through the Generalized Least Squares (GLS) Estimator method . From the results of the data processing, it was obtained that the model is influenced by economic growth, life expectancy, open unemployment rate, and labor force participation rate. From the results of the analysis of 2 (two) models, it was tested significantly and affected poverty in South Kalimantan Province in 2016-2020.  Keywords:   Poverty, Data Regression Panel, Generalized Least Square Method (GLS).
PEMODELAN REGRESI DATA PANEL PADA TINGKAT PARTISIPASI ANGKATAN KERJA PEREMPUAN DI PROVINSI KALIMANTAN SELATAN Putri Norhikmah; Fuad Muhajirin Farid; Aprida Siska Lestia
RAGAM: Journal of Statistics & Its Application Vol 1, No 1 (2022): RAGAM: Journal of Statistics and Its Application
Publisher : Universitas Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/ragam.v1i1.7383

Abstract

Women’s Labor Force Participation Rate (LFPR) is an indication that can shows how much participation of women in the process development. The purpose of this study is to provide an overview of LFPR women in the Province of South Kalimantan, explaining the expected variables influence on women’s LFPR in South Kalimantan Province and determine the best model. This research data is sourced from the Centra Statistics Agency of South Kalimantan Province with a time period of 2017-2020. Variable independen research, namely female workers, female residents who are still in school and taking care of the household, the average length of schooling for women, female population according to the highest education ever graduate from senior high school above, female household heads, status of married and unmarried women marriage, district/city minimum wage, human development index women and regional domestic income growth at constant prices while the dependent variable is female LFPR. The results of data analysis, can be conclude that the Fixed Effect Model as the best model of panel regression. Women’s LFPR in South Kalimantan Province by producing two recommendation with Fixed Effect Model an R-Squared in the first model of 99,40%.Keywords:  Women’s LFPR, Panel Data Regression, South Kalimantan
Co-Authors Ahmad Taufik Amalia, Zharfa Rizqi Andriani, Asfia Ariandy Hermawan Azkia Azkia Azkia Khairal Jamil Balya, Muhammad Afief Dewi Anggraini Dewi Sri Susanti Faisal Faisal Fitriani Fitriani Fuad Muhajirin Farid Fuad Muhajirin Farid Gunawan, I Wayan Ari Hijriati, Naimah Idris, Moch Idris, Mochammad Kasim Alfarisi Lissa, Hermei Maria Ulfah Muhammad Firdaus Muhammad Meidy Maulana Nabila Septiani Nadya Pratiwi Noor Baitirahmah Noor Jannah, Noor Nur Salam Nur Salam Oktaviani, Yeni Rahma Pardi Affandi Putri Norhikmah Riska Fitria Rusidawati Rusidawati Saman Abdurrahman Sa’adh, Yalela Sekar Wahyuningtias Shiddiq, Muhammad Mahfuzh Siti Jubaidah Syifa Ajeria Thaibatun Nissa Thresye Thresye Tri Puspa Lestari Winda Adinda Tanjung Wuri Setyana Sari Yogi Apriyanto Yuana Sukmawaty Yuni Yulida