Analisis Ketimpangan Distribusi Pendapatan Berdasarkan Faktor Spasial, Sosial, dan Ekonomi

Masrurhoh, Lailatul (2026) Analisis Ketimpangan Distribusi Pendapatan Berdasarkan Faktor Spasial, Sosial, dan Ekonomi. Other thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Ketimpangan distribusi pendapatan merupakan salah satu permasalahan pembangunan yang dapat memengaruhi kesejahteraan masyarakat dan pemerataan pembangunan wilayah. Perbedaan karakteristik sosial, ekonomi, dan aksesibilitas antarwilayah menyebabkan tingkat ketimpangan pendapatan memiliki pola yang berbeda secara spasial. Penelitian ini bertujuan untuk menganalisis pola ketimpangan distribusi pendapatan berdasarkan faktor spasial, sosial, dan ekonomi pada kabupaten/kota di Provinsi Daerah Istimewa Yogyakarta (DIY) dan Provinsi Jawa Tengah. Variabel dependen yang digunakan yaitu Gini Ratio, sedangkan variabel independen meliputi Upah Minimum Kabupaten/Kota (UMK), Indeks Pembangunan Manusia (IPM), Tingkat Pengangguran Terbuka (TPT), persentase kemiskinan, jarak ke gerbang tol, jarak ke bandara, jumlah stasiun, jumlah tempat wisata, dan Produk Domestik Regional Bruto (PDRB). Metode yang digunakan meliputi Ordinary Least Squares (OLS), uji multikolinearitas, Global Moran’s I, dan Geographically Weighted Regression (GWR). Hasil OLS menunjukkan nilai R² sebesar 0,594 yang menunjukkan model mampu menjelaskan 59,4% variasi ketimpangan pendapatan. Analisis Global Moran’s I menghasilkan nilai Moran’s Index sebesar 0,256 yang menunjukkan adanya pola spasial mengelompok (clustered) yang signifikan secara statistik. Hasil GWR menunjukkan nilai R² sebesar 0,600 sehingga model mampu menjelaskan 60% variasi ketimpangan pendapatan. Variabel yang memiliki pengaruh paling besar terhadap kenaikkan ketimpangan pendapatan yang ditinjau berdasarkan nilai koefisien (β) adalah Indeks Pembangunan Manusia (IPM), Tingkat Pengangguran Terbuka (TPT), Jarak ke Gerbang Tol dan Jumlah Tempat Wisata. Sedangkan variabel lainnya memiliki pengaruh yang bervariasi pada setiap wilayah. Hasil penelitian menunjukkan bahwa pendekatan spasial melalui GWR lebih mampu menggambarkan variasi pengaruh faktor antarwilayah dibandingkan model global serta dapat menjadi dasar dalam penyusunan kebijakan pembangunan yang lebih tepat sasaran guna mendukung pengurangan ketimpangan antarwilayah sesuai SDGs tujuan ke-10.
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Income distribution inequality is one of the development issues that can affect public welfare and the equitable distribution of development across regions. Differences in social and economic characteristics and accessibility among regions result in spatially distinct patterns of income inequality. This study aims to analyze patterns of income distribution inequality based on spatial, social, and economic factors in regencies and cities in the Special Region of Yogyakarta (DIY) and Central Java Province. The dependent variable used is the Gini coefficient, while the independent variables include the Regency/City Minimum Wage (UMK), the Human Development Index (HDI), the Open Unemployment Rate (TPT), the poverty rate, distance to a toll gate, distance to an airport, number of train stations, number of tourist attractions, and Gross Regional Domestic Product (GRDP). The methods used include Ordinary Least Squares (OLS), multicollinearity test, Global Moran’s I, and Geographically Weighted Regression (GWR). The OLS results show an R² value of 0.594, indicating that the model explains 59.4% of the variation in income inequality. The Global Moran’s I analysis yielded a Moran’s Index value of 0.256, indicating the presence of a statistically significant clustered spatial pattern. The GWR results showed an R² value of 0.600, meaning the model explains 60% of the variation in income inequality. The variables with the greatest influence on the increase in income inequality, as assessed based on their coefficient (β) values, are the Human Development Index (HDI), the Open Unemployment Rate (TPT), Distance to the Toll Gate, and the Number of Tourist Attractions. Meanwhile, the other variables have varying influences across different regions. The research results indicate that the spatial approach using GWR is better able to describe variations in the influence of factors across regions compared to global models and can serve as a basis for formulating more targeted development policies to support the reduction of interregional inequality in line with SDG Goal 10.

Item Type:	Thesis (Other)
Uncontrolled Keywords:	Geographically Weighted Regression, Gini Ratio, Global Moran’s I,Ketimpangan Pendapatan, Geographically Weighted Regression, Gini Ratio, Global Moran’s I, IncomeInequality.
Subjects:	G Geography. Anthropology. Recreation > GF Human ecology. Anthropogeography H Social Sciences > HA Statistics > HA30.6 Spatial analysis H Social Sciences > HA Statistics > HA31.3 Regression. Correlation. Logistic regression analysis.
Divisions:	Faculty of Civil, Planning, and Geo Engineering (CIVPLAN) > Geomatics Engineering > 29202-(S1) Undergraduate Thesis
Depositing User:	Lailatul Masrurhoh
Date Deposited:	22 Jul 2026 07:30
Last Modified:	22 Jul 2026 07:30
URI:	http://repository.its.ac.id/id/eprint/136287

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