ORDINAL LOGISTIC REGRESSION MODEL FOR HUMAN DEVELOPMENT INDEX DATA IN PAPUA AND WEST PAPUA PROVINCES

Nabilla Rida Tri Nisa(1*), Novia Amilatus Solekha(2), Abdullah Fahmi(3), Panji Jilblathar(4), Purhadi Purhadi(5)


(1) Department of Graphic Engineering, Faculty of Industrial Technology, Politeknik Negeri Media Kreatif
(2) Institut Teknologi Sepuluh Nopember
(3) Department of Statistics , Faculty of Science and Data Analytics, Institut Teknologi Sepuluh Nopember
(4) Department of Statistics , Faculty of Science and Data Analytics, Institut Teknologi Sepuluh Nopember
(5) Department of Statistics , Faculty of Science and Data Analytics, Institut Teknologi Sepuluh Nopember
(*) Corresponding Author

Abstract


The Human Development Index (HDI) is a key indicator used to measure the quality of economic development, particularly the degree of human development. In 2019, the HDI for Papua Province was 60.84, while West Papua Province recorded a value of 64.70. According to the Central Statistics Agency, these figures indicate that Papua and West Papua are the provinces with the lowest HDI in Indonesia. This research aims to identify the factors influencing the HDI in Papua and West Papua Provinces in 2019 using an ordinal logistic regression approach. The study utilizes secondary data from the Central Statistics Agency for both provinces. The results indicate that the model developed is appropriate, with the Open Unemployment Rate (TPT) and average per capita expenditure being significant factors influencing HDI. The model's effectiveness is evidenced by an Akaike Information Criterion (AIC) value of 28.978

Full Text:

PDF

References


Ayu. LD, Putri. EM, and Indrasetianingsih. A. “Modeling the Human Development Index and Gender Development Index in Indonesia using the Probit Regression Approach Bivariate” . Journal of Mathematics, Statistics and Computing, 1-4. 2020.

Sari. M, and Purhadi. “Pemodelan Indeks Pembangunan Manusia Provinsi Jawa Barat, Jawa Timur Dan Jawa Tengah Tahun 2019 Dengan Menggunakan Metode Regresi Logistik Ordinal”, Jurnal Gaussian, 10 (1). 2021.

Nefri. N, and Pramesti. W. “Pemodelan Regresi Logistik Ordinal Terhadap Indeks Pembangunan Manusia (IPM) Di Jawa Tengah Tahun 2021”. Prosiding Seminar Nasional Hasil Riset dan Pengabdian, E-ISSN: 2776-5105. 2021.

Christyadi. S, Satriya. A, and Goejantoro. R. “ Pemodelan Indeks Pembangunan Manusia (IPM) Menggunakan Analisis Regresi Probit (Studi Kasus: Indeks Pembangunan Manusia (IPM) di Pulau Kalimantan Tahun 2017)”, Jurnal EKSPONENSIAL Volume 11(2), Nopember 2020.

Agresti, A, Categorical Data Analysis (2nd ed). New Jersey: John Wiley & Sons, Inc. 2002.

Budyanra. B, and Azzahra. GN, “Penerapan Regresi Logistik Ordinal Proportional Odds Model pada Analisis Faktor-Faktor yang Mempengaruhi Kelengkapan Imunisasi Dasar Anak Balita di Provinsi Aceh Tahun 2015”, MEDIA STATISTIKA 10(1) :37-47. 2017.

Fauzan. A, Rahmah. AH, and Pradana. SC, “Model Regresi Logistik Ordinal untuk Menentukan Faktor Pengambilan Keputusan Calon Mahasiswa Memilih Program Studi Statistika”, Statistika, Vol. 18 No. 1, 85 – 96. 2018

Akbar, SJ, A. Mukarromah and L. Paramita. “Ordinal Logistic Regression

Bagging on the Nutritional Status of Toddlers”. Statistical Media, 3(2): 103-116. 2010

Agresti, A. Analysis of Ordinal Categorical Data (2nd ed). New Jersey: John Wiley & Sons, Inc. 2010

Hosmer , D.W. & Lemeshow . Applied Logistics Regression . New York

: John Wiley and Sons , Inc. 2000

Hosmer , D.W., Lemeshow , S., & Sturdivant . Applied Logistics Regression (3rd ed ) . New York : John Wiley & Sons , Inc. 2013.

BPS. Human Development Index 2015. Jakarta: Central Statistics Agency. 2015.

Hocking. R. R, Method and Applications of Linear Models (2nd Edition ed), New York: John Wiley and Sons, Inc, 1996.

Bozdogan. H. Akaike's information criterion and recent developments in information complexity. Journal of Mathematical Psychology. 44(1). 62–91. https://doi.org/10.1006/jmps.1999.1277. 2000

Gujarati. D. N. & Porter. D. C. Basic Econometrics. 5th edition. McGrawHill. New York. 2009.


Article Metrics

Abstract view : 39 times
PDF - 0 times

DOI: https://doi.org/10.26714/jsunimus.12.2.2024.%25p

Refbacks



Copyright (c) 2024 Jurnal Statistika Universitas Muhammadiyah Semarang

Editorial Office:
Department of Statistics
Faculty Of Mathematics And Natural Sciences 
Universitas Muhammadiyah Semarang

Jl. Kedungmundu No. 18 Semarang Indonesia



Published by: 
Department of Statistics Universitas Muhammadiyah Semarang

View My Stats

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License