Last modified: 2023-06-22
Abstract
Pulau Sumatera terdiri dari 10 provinsi, terbagi menjadi tiga bagian wilayah, yaitu Sumatera Bagian Utara, Sumatera Bagian Tengah, dan Sumatera Bagian Selatan. Jumlah penduduk miskin tertinggi di Pulau Sumatera berada pada wilayah Sumatera Bagian Selatan (Sumbangsel) yang mencapai 2,88 juta orang. Kemiskinan adalah suatu konsep menyeluruh yang memiliki lima dimensi, yaitu kemiskinan, ketidakberdayaan, kerentanan menghadapi situasi darurat, ketergantungan, dan keterasingan baik secara geografis maupun sosiologis. Salah satu metode yang dapat dilakukan untuk menganalisis permasalahan data kemiskinan adalah analisis regresi data panel yang merupakan penggabungan dari dua data, yaitu data lintas individu dan deret waktu. Sehingga diharapkan mampu mengendalikan keragaman individu dan menghasilkan informasi lebih mendalam dan menyeluruh, baik keterkaitan antar variabelnya maupun perkembangannya dalam periode waktu tertentu. Penelitian ini bertujuan untuk memodelkan data panel kemiskinan di Sumbangsel dengan mengguanakan tiga metode estimasi ,yaitu Common Effect Model (CEM), Fixed Effect Model (FEM) dan Random Effect Model (REM). Uji spesifikasi model menunjukkan bahwa model terbaik untuk mengestimasi persentase penduduk miskin di wilayah Sumbangsel adalah Fixed Effect Model (FEM), dengan nilai R2 =75,57%. Variabel-variabel yang berpengaruh secara signifikan terhadap persentase kemiskinan di wilayah Sumbangsel dengan model FEM adalah tingkat pengangguran terbuka , angka harapan hidup (), dan rata-rata lama sekolah
Poverty is still a major problem on the island of Sumatra, despite having abundant natural resource potential, such as mining and plantation products. Sumatra Island consists of 10 provinces, which are divided into three regions, namely Northern Sumatra, Central Sumatra, and Southern Sumatra. The highest number of poor people on the island of Sumatra is in the Southern Sumatra region which reaches 2.88 million people. Poverty is an integrated concept that has five dimensions, namely poverty, powerlessness, vulnerability to face emergencies, dependency, and alienation both geographically and sociologically. One method that can be used to analyze poverty data problems is panel data regression analysis which is a combination of two data, namely cross-sectional data and time series data. individuals and is expected to produce more in-depth and comprehensive information, both the interrelationships between the variabels and their development within a certain period of time. The panel data used is data related to poverty and includes a total of 60 districts in the southern Sumatra region starting from 2018 to 2020. This study aims to model poverty panel data in Southern Sumatra. Three estimation methods are used in the panel data regression, including the Common Effect Model (CEM), Fixed Effect Model (FEM) and Random Effect Model (REM) From the results of the model specification test it is found that the best model for estimating the percentage of poor people in the Southern Sumatra region is the Fixed Effect Model (FEM), with a value of= 75.57%. The results of the significance test show that the variabels that significantly influence the percentage of poverty in the Southern Sumatra region using the FEM model are the open unemployment rate (
), life expectancy (
), and average length of schooling (
).