Penerapan Model Regresi Data Panel : Determinan Ketimpangan Capaian Pendidikan Di Kawasan Timur Indonesia (Kti) 2015-2019

Nurmutiazifah, A; Yuniasih, Aisyah Fitri

doi:10.34123/semnasoffstat.v2020i1.705

Cited by 4 publications

(4 citation statements)

References 3 publications

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“…From the results of research with ethnic variables, indicates that there is an inequality in the average length of schooling in Indonesia, education in Java is far more advanced than outside Java (Yuniasih, 2019). So that the Javanese female labor force are able to compete in the formal employment sector because the educational administration requirements can be easily achieved.…”

Section: Resultsmentioning

confidence: 99%

Does Informal Sector Suitable for Female Labor?

Yuniashri

Susilo

Wahyudi

2023

jejak

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The existence of SDGs program which supported by the demographic bonus era provides potential for female labor force, but the fact in Indonesia is that there is an inequality in the number of working female labor force compared to men, especially the field of work dominated by women is threatened by industrial automation 4.0. The purpose of this study is to analyze how the characteristics of women to the opportunities in the informal and formal job that seen from age, marital status, wages, length of education taken, ethnicity, and area of residence. The method used in this study is binary logistic regression with IFLS 5 data sources. The results showed that women who decided to work in the informal sector were women of older age, married women, women who studied longer, women with Batak and Sasak ethnicities, and women who lived in rural areas. The Indonesian government is expected to be able to improve policies for informal sector workers including decent wages, social security and health, and legal protection in order to achieve Indonesian goals according to SDGs agenda.

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Section: Resultsmentioning

confidence: 99%

Does Informal Sector Suitable for Female Labor?

Yuniashri

Susilo

Wahyudi

2023

jejak

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“…Kemiskinan di suatu negara merefleksikan tingkat kesejahteraan penduduknya. Semakin rendah tingkat kemiskinan di suatu negara, maka dapat dikatakan semakin sejahtera penduduknya [5]. Di Indonesia sendiri, penurunan angka kemiskinan masih menjadi permasalahan utama dalam proses pembangunan.…”

Section: Pendahuluanunclassified

Pengaruh Infrastruktur terhadap Kemiskinan: Analisis Data Panel 34 Provinsi di Indonesia

Andrianus

Alfatih

2023

INFEB

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This study aims to analyze how the influence of infrastructure consisting of sanitation, electricity and roads on poverty levels in Indonesia, either simultaneously or partially. This study uses a quantitative method in the form of multiple regression analysis with panel data. The type of data used is secondary data from 34 provinces in Indonesia during the 2015-2019 period obtained from the Central Statistics Agency which includes: data on the percentage of the number of poor people, data on the length of roads and the area of the province, data on the percentage of households that have access to PLN electricity, and data on the percentage of households that have access to proper sanitation services. The results of the analysis using a random effect model approach show that sanitation, electricity and road infrastructure have a significant negative effect on poverty levels. This means that an increase in each infrastructure has an effect on reducing the percentage of poor people in Indonesia. Thus, it is evident that the increase in each variable of sanitation, electricity and roads has a significant effect on reducing the percentage of the number of poor people in Indonesia.

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“…Hal ini mengindikasikan bahwa adanya ketimpangan pencapaian pendidikan di KTI. Rendahnya RLS KTI diikuti dengan rendahnya pendapatan perkapita dan persentase penduduk miskin yang tinggi di wilayah KTI [10]. Namun, berdasarkan penelitian yang dilakukan oleh Kapriaji dan Siswidiyanto [11], rasio ketersediaan SMA/MA di KTI lebih baik dibandingkan wilayah KBI.…”

Section: Sumber: Bps (2021) Diolah Gambar 2 Gini Ratio Provinsi DI In...unclassified

Grouping of Regencies/Municipalities in Eastern Indonesia in 2021 Based on Socio-Economic Indicators

Firnanda,

Wijayanto

2023

SISTEMASI

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Perbedaan kondisi sosial, ekonomi, demografi dan sumber daya pada masing-masing daerah mampu menyebabkan ketimpangan, sehingga perlu mendorong pembangunan ekonomi sesuai kemampuan yang dimiliki oleh daerah tersebut. Pentingnya melihat indikator sosial ekonomi yang menjadi target pembangunan, khususnya di Kawasan Timur Indonesia (KTI). Penelitian ini menggunakan dua metode non hierarki, yaitu K-Means dan K-Medoids. Dalam penelitian ini dilakukan Principal Component Analysis (PCA) menghasilkan 3 faktor. Penentuan jumlah cluster menggunakan validitas internal dan stabilitas menunjukkan bahwa metode K-Means dengan jumlah cluster sebanyak 2 menghasilkan cluster yang paling optimal. Cluster 1 terdiri dari 152 kabupaten/kota, sedangkan cluster 2 terdiri dari 80 kabupaten/kota. Cluster 1 memiliki karakteristik sarana dan prasarana serta ekonomi di atas rata-rata, sementara kualitas manusia nya masih di bawah rata-rata.

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Penerapan Model Regresi Data Panel : Determinan Ketimpangan Capaian Pendidikan Di Kawasan Timur Indonesia (Kti) 2015-2019

Cited by 4 publications

References 3 publications

Does Informal Sector Suitable for Female Labor?

Does Informal Sector Suitable for Female Labor?

Pengaruh Infrastruktur terhadap Kemiskinan: Analisis Data Panel 34 Provinsi di Indonesia

Grouping of Regencies/Municipalities in Eastern Indonesia in 2021 Based on Socio-Economic Indicators

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