Nurfadila, Monika Refiana
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Identifikasi Faktor-Faktor Pengaruh Indeks Gini Ratio Menggunakan Regresi Logistik Ordinal Nurfadila, Monika Refiana; Intan, Putroue Keumala
JURNAL ILMIAH MATEMATIKA DAN TERAPAN Vol. 20 No. 1 (2023)
Publisher : Program Studi Matematika, Universitas Tadulako

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22487/2540766X.2023.v20.i1.16258

Abstract

Ketimpangan pendapatan menjadi permasalaan yang masih dialami oleh negara Indonesia. Perlu dilakukan suatu upaya untuk menangani ketimpangan pendapatan dengan menurunkan nilai indeks gini ratio. Hal tersebut dapat dilakukan dengan meminimalisir faktor penyebab tingginya nilai indeks gini ratio. Penelitian ini bertujuan untuk mengidentifikasi faktor penyebab tingginya indeks gini ratio serta mengetahui besarnya pengaruh faktor indeks gini ratio menggunakan metode regresi logistik ordinal. Penelitiian ini menggunakan variabel dependen berupa indeks gini ratio sedangkan untuk variabel independennya yaitu IPM, pengangguran terbuka, upah minimum provinsi, PDRB, jumlah penduduk dan presentase penduduk miskin. Berdasarkan hasil analisis didapatkan bahwa faktor-faktor yang berpengaruh positif dan signifikan terhadap indeks gini ratio yaitu IPM, jumlah penduduk serta presentase penduduk miskin. Model regresi logistik ordinal yang didapatkan mampu menjelaskan pengaruh terhadap indeks gini ratio sebesar 61,7%.Kata kunci : Ketimpangan Pendapatan, Indeks Gini Ratio, Regresi Logistik Ordinal
Identifying Significant Factors Affecting the Human Development Index in East Java Using Ordinal Logistic Regression Model Farida, Yuniar; Nurfadila, Monika Refiana; Yuliati, Dian
JTAM (Jurnal Teori dan Aplikasi Matematika) Vol 6, No 3 (2022): July
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jtam.v6i3.8301

Abstract

The achievement of human development can be reviewed from the Human Development Index (HDI), which is sourced from indicators of health, education, and state income. East Java Province is the second-most populous province in Indonesia which has a high work intensity in economic aspects and abundant natural and human resources. However, judging from the level of the human development index, East Java Province occupies the lowest position compared to other provinces on the island of Java. This study aims to identify significant factors affecting East Java's HDI using ordinal logistic regression. The data from Indonesia Statistics (Indonesian: Badan Pusat Statistik, BPS) of East Java province in 2020 includes seven variables, namely Gross Regional Domestic Product (GRDP), high school participation rate, infant mortality rate, health facilities, population density, labor force participation rate, and open unemployment rate. This study produced two ordinal logistic regression models in medium category HDI and high category HDI with a classification accuracy value of 97.37%. From this model obtained, a significant factor affecting the HDI of East Java is the participation rate of high school and health facilities.