Economic inequality and its impact on human development: insight of Banten Province 2011-2015

Septianingrum, Resiska; Aditya, Bagas; Wijaya, Andy Putra; Irshabdillah, M. R.; Husna, Nada Alia; Putri, Ratih Fitria

doi:10.1088/1755-1315/451/1/012107

Cited by 4 publications

(4 citation statements)

References 4 publications

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“…In Septianingrum, et al (2020), the results of the study suggest that GRDP has a positive and significant effect on HDI. Where the relationship between GRDP and HDI can be described in a theoretical perspective through the mechanism trickle down effect.…”

Section: Resultsmentioning

confidence: 77%

“…Based on research conducted by Ogbebor, et al (2020) and Pangesti and Susanto (2018), the results show that inflation has a negative and insignificant effect on HDI. Research conducted by Septianingrum, et al (2020), Zainuddin (2015), and Ramadona, et al (2019) shows that the results show that the GRDP variable has a positive and significant effect on HDI.…”

Section: Introductionmentioning

confidence: 95%

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Determinant of HDI in Yogyakarta Special Region Province

Annisa¹

2022

jef

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Yogyakarta Special Region (DIY) occupies the second position of high categorical HDI in Indonesia. The UMP, which is the benchmark for the number of wages given to workers, has the lowest amount in Indonesia. Several other factors that were thought to have influenced the high in HDI were inflation, GRDP, and LFPR. This study aims to determine and analyze the factors that influence HDI in DIY. The type of data used in this study is secondary data. The data used are sourced from BPS, Indonesian Statistics Report, Yogyakarta Labour Affair Office and GlobalDataLab. The research method used is multiple regression analysis time series for the period 1990-2019 DIY. The variables used in this study are HDI, Inflation, GRDP, UMP, and LFPR. The results showed that inflation has a negative and not significant effect on HDI. GDRP, UM,P and LFPR have a positive and significant effect on HDI. Daerah Istimewa Yogyakarta (DIY) menempati posisi IPM tinggi kedua di Indonesia. UMP yang menjadi tolak ukur besarnya upah yang diberikan kepada pekerja memiliki besaran paling rendah di Indonesia. Beberapa faktor lain yang diduga mempengaruhi tingginya IPM adalah inflasi, PDRB dan TPAK. Penelitian ini bertujuan untuk mengetahui dan menganalisis faktor-faktor yang mempengaruhi IPM di DIY. Jenis data yang digunakan bersumber dari BPS, Laporan Statistik Indonesia, Dinas Tenaga Kerja DIY dan GlobalDataLab. Metode penelitian yang digunakan adalah analisis regresi berganda time series periode 1990-2019 DIY. Variabel yang digunakan dalam penelitian ini adalah IPM, Inflasi, PDRB< UMP dan TPAK. Hasil penelitian menunjukkan bahwa inflasi berpengaruh negatif dan tidak signifikan terhadap IPM. PDRB, UMP dan TPAK berpengaruh positif dan signifikan terhadap IPM.

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Section: Resultsmentioning

confidence: 77%

Section: Introductionmentioning

confidence: 95%

Determinant of HDI in Yogyakarta Special Region Province

Annisa¹

2022

jef

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“…Analisis ini hanya memberikan penjelasan mengenai sebaran PDRB per kapita dalam satu provinsi. Dari hasil analisis akan diperoleh angka 0 sampai dengan 1 dimana, apabila hasil mendekati angka 1 maka terjadi ketimpangan artinya, pertumbuhan ekonomi tidak merata dan apabila mendekati angka nol maka tidak terjadi ketimpangan artinya pertumbuhan ekonomi terjadi secara merata (Islami & SBM, 2018;Luthfiyah & Tallo, 2020;Maulana, 2019;Septianingrum et al, 2020). Indeks Williamson dapat dihitung menggunakan rumus: (Ibrahim, 2018;Rizani, 2019;Rosiadi, 2020).…”

Section: Indeks Williamson (Iw)unclassified

Analisis Sektor Ekonomi Provinsi Gorontalo Tahun 2017-2022

Olii,

Sudirman,

Halid

2023

Ekuitas

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Indonesia, as an archipelago, has different regional characteristics, so the problem of regional inequality cannot be avoided. The central government authorizes local governments to develop the potential of the region so that each region is required to be able to independently improve its economy. Gorontalo province, as a province of expansion in 2000, is in a strategic location that has great potential in the agricultural sector, as well as in mariculture an agriculture. The research objective is to determine the condition of economic inequality in Gorontalo province and the leading sectors in each district/city of Gorontalo province. Using time series data from 2017-2022, inequality is analyzed using the Williamson Index (IW), and to determine leading sectors, location quotient (LQ) analysis is used. The results show that the level of inequality in Gorontalo province is close to zero, which means that the condition of the level of income and welfare of the population is evenly distributed because the majority of population employment is still dominated by the agriculture, sector, which is the leading sector in Gorontalo, Boalemo, and North Gorontalo districts, and the trade sector, which is the leading sector in Boalemo and Bonebolango districts

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“…Basic and non-basic sectors can be calculated using several methods, including the Location Quotient (LQ) and Shift-Share methods. The LQ method is carried out by comparing the roles between sectors in regional economic activities [4]. In contrast, the Shift-Share method is used to determine the development of the economic sector and its comparison with other agricultural sectors.…”

Section: Introductionmentioning

confidence: 99%

Study of agricultural economic potential in West Kalimantan using Regional Analysis Techniques

Nurulhuda¹,

Askarina²,

Romadhoniastri³

et al. 2021

E3S Web Conf.

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The agricultural resource is one of the most critical sectors in the economy, which contributes a high portion of the growth and development of a particular region. Differences in characteristics and potential between regions give rise to the basic and non-basic sectors, which then affect income contribution. This research aims to analyze the economic potential of the agricultural sector of the regencies and cities in West Kalimantan Province as basic or non-basic sector. Both basic and non-basic sector analysis can be carried out using quantitative-descriptive methods using Shift-Share and Location Quotient (LQ) analysis. The analysis was carried out using secondary data from the Central Statistics Agency (BPS) publication from 2015 to 2020. The results of the LQ analysis show the agricultural sector in Sambas, Bengkayang, Landak, Mempayah, Sanggau, Ketapang, Sintang, Kapuas Hulu, Sekadau, and Kayong Utara are the basic sector. Meanwhile, the agricultural sector in Kubu Raya, Pontianak, and Singkawang are non-basic sector. Agriculture in Melawi Regency has changed from a basic sector in 2015, to a non-basic sector in 2020. The results of the Shift-Share analysis show the agricultural sector in Sambas, Bengkayang, Landak, Mempayah, Sanggau, Ketapang, Kapuas Hulu, Sekadau, Kubu Raya, Pontianak and Singkawang have progressive or advanced growth, while Sintang, Melawi and Kayong Utara have slowed growth.

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Economic inequality and its impact on human development: insight of Banten Province 2011-2015

Cited by 4 publications

References 4 publications

Determinant of HDI in Yogyakarta Special Region Province

Determinant of HDI in Yogyakarta Special Region Province

Analisis Sektor Ekonomi Provinsi Gorontalo Tahun 2017-2022

Study of agricultural economic potential in West Kalimantan using Regional Analysis Techniques

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