Analisis Faktor-Faktor Yang Mempengaruhi Tingkat Ketimpangan Pendapatan Di Pulau Jawa

Farhan, Muhammad; Sugianto, Sugianto

doi:10.54443/sibatik.v1i4.29

Cited by 7 publications

(6 citation statements)

References 1 publication

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“…According to Hindun's (2019) research, education, unemployment, and poverty, all have a 22.37% influence income inequality in Indonesia, with the remaining 77.63% explained by factors outside of research. The condition is consistent with the research findings of Farhan and Sugianto (2022) that poverty harms income inequality in Java Island. Khoirunurrofik & Fitriatinnisa (2021) expects that developing countries will have high levels of poverty and inequality.…”

Section: Introductionsupporting

confidence: 91%

Do Government Policies and Socioeconomic Conditions Affect Income Inequality?

Wahyuningrum

Aisyah

2023

EDAJ

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The problem that is often faced by developing countries is high-income inequality among the population. On the other hand, the development of digital technology occurs very quickly and encourages the community to play a more active role in economic activities. This condition needs to be further explored, especially considering its relation to income inequality in Indonesia. This study aims to determine the effect of government policies and socioeconomic conditions on income inequality in Indonesia in the 2019-2021 period by analyzing secondary data in 34 provinces in Indonesia. The analytical method uses panel data regression with the selected model of the fixed effect model. The data was taken from the Central Bureau of Statistics, each provincial government's Directorate General of Finance, and the Ministry of Manpower of the Republic of Indonesia. The results showed that the number of poor people significantly positively affected income inequality and regional minimum wages, and the information and communication technology development index negatively affected income inequality. In contrast, the human development index and social assistance spending had no impact on income inequality. The government must improve poverty alleviation programs to reduce the income inequality gap while expanding the accessibility of Information and Communication Technology (ICT) to provide a better quality of life for the people. This study enriches previous research on the effect of socioeconomic conditions on income inequality by adding the newly developed ICT development index variable

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Section: Introductionsupporting

confidence: 91%

Do Government Policies and Socioeconomic Conditions Affect Income Inequality?

Wahyuningrum

Aisyah

2023

EDAJ

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“…Selain itu, penelitian ini didukung pada penelitian (Suryani & Woyanti, 2021) dalam penelitiannya dimana hasil penelitiannya juga sama dengan penelitian ini yaitu IPM berpengaruh negatif terhadap ketimpangan distribusi pendapatan di Provinsi D.I Yogyakarta tahun 2010 -2018. Hal yang sama juga diperoleh (Farhan & Sugianto, 2022) pada penelitiannya dimana hasil penelitiannya juga sama dengan penelitian ini yaitu IPM berpengaruh negatif terhadap ketimpangan pendapatan di Pulau Jawa periode 2014 -2020.…”

Section: Pembahasan Hasil Penelitian Pengaruh Pertumbuhan Ekonomi Ter...unclassified

Analisis Faktor – Faktor Yang Mempengaruhi Ketimpangan Pendapatan Masyarakat Di Sumatera Utara

Silaban,

Sianturi,

Br.Sembiring

2024

Niaga

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Ketimpangan merupakan salah satu penghambat dalam pembangunan ekonomi di setiap negara. Perbedaan pendapatan terlihat membuat jarak antara kelompok kaya dan miskin semakin jauh dan kesejahteraan secara tidak merata menunjukkan masih banyak kelas masyarakat atas dengan bawah. Pada penelitian ini dimaksudkan untuk melihat pengaruh dari pertumbuhan ekonomi, IPM dan tingkat pengangguran terbuka terhadap ketimpangan pendapatan masyarakat di Provinsi Sumatera Utara. Objek penelitian ini yaitu 33 Kab/Kota di Provinsi Sumatera Utara. Penelitian ini berupa penelitian kuantitatif dengan menggunakan metode regresi data panel. Pengolahan data dengan perangkat lunak E-views 12. Dari penelitian yang dilakukan diperoleh hasil Pertumbuhan Ekonomi berpengaruh positif dan tidak signifikan terhadap Ketimpangan Pendapatandengan nilai probability 0,2952. Variabel IPM berpengaruh negatif dan signifikan terhadap Ketimpangan Pendapatan dengan nilai probability 0,0000. Variabel Tingkat pengangguran Terbuka berpengaruh positif dan tidak signifikan terhadap Ketimpangan Pendapatan dengan nilai probabilitynya sebesar 0,7193. Secara simultan Pertumbuhan Ekonomi, IPM, dan Tingkat Pengangguran Terbuka berpengaruh signifikan terhadap ketimpangan pendapatan serta ketiga variabel yang diteliti memiliki kontribusi sebesar 70,57% dan sisanya dijelaskan oleh variabel lain diluar penelitian ini.

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“…Pada penelitian terdahulu, tinggi rendahnya niai IPM ini menjadi sebuah permasalahan pembangunan di Jawa Barat karena hanya direpresentasikan dengan komponen utama IPM yaitu UHH, RLS, HLS, dan pengeluaran perkapita disesuaikan (Atika Nurani Ambarwati, 2019). Sejatinya banyak sekali faktor lain yang dapat mempengaruhi IPM seperti ketimpangan pendapatan memiliki pengaruh yang signifikan terhadap IPM (Farhan & Sugianto, 2022). Faktor lain yang dapat mempengaruhi IPM adalah Indeks Pembangunan Gender (IPG) dan upah minumum kabupaten/kota (Ramadhani & Utomo, 2023).…”

Section: Pendahuluanunclassified

Pembentukan Klaster Terhadap Indeks Pembangunan Manusia Di Wilayah Jawa Timur

Ansori,

Muhaimin,

Terza

2024

SCI TECH ED MATH

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The Human Development Index (HDI) is one of the efforts to achieve the Sustainable Development Goals (TPB) with HDI components including health, education and a decent standard of living. Referring to the Central Statistics Agency, it always increases from 2010 to 2022, but there are still several regions in East Java that have low HDI values. Based on this, it is necessary to carry out analysis using clustering techniques so that we can find out more deeply about the characteristics of each district or city in East Java. The research method used is by collecting data which includes HDI, UHH, RLS, HLS per capita expenditure values, income inequality, HDI, city minimum wage, GRDP, number of poor people, open unemployment rate, population, and labor force participation rate. After obtaining the data, data exploration and cleaning was carried out, principal component analysis (PCA), factor analysis, modeling using K-Means and DBSCAN, and silhouette calculations were carried out. The results show that the K-Means model has 3 clusters. Cluster 1 has a purple color with superior characteristics in all aspects except the HDI value, GRDP, and the number of poor people. Cluster 2 has a green color with less superior characteristics in terms of UHH, RLS, HLS, real per capita expenditure, income inequality, and IPG. And cluster 3 in yellow has superior characteristics in terms of UHH, RLS, HLS, real per capita expenditure, income inequality, and IPG. East Java Province always experiences increasing HDI values, but there are still disparities between one district or city and another as shown by the K-Means silhouette value of 0.43

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Analisis Faktor-Faktor Yang Mempengaruhi Tingkat Ketimpangan Pendapatan Di Pulau Jawa

Cited by 7 publications

References 1 publication

Do Government Policies and Socioeconomic Conditions Affect Income Inequality?

Do Government Policies and Socioeconomic Conditions Affect Income Inequality?

Analisis Faktor – Faktor Yang Mempengaruhi Ketimpangan Pendapatan Masyarakat Di Sumatera Utara

Pembentukan Klaster Terhadap Indeks Pembangunan Manusia Di Wilayah Jawa Timur

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