COMPARING FOUR GENERALIZED LINEAR MODELING LINK FUNCTIONS OF ANALYZING FACTORS AFFECTING THE HUMAN DEVELOPMENT INDEX (HDI)

https://doi.org/10.22146/jmt.101505

Rossa Fitria Halim(1*), Renanta Dzakiya Nafalana(2), Adityo Wahyu Saputro(3), Mohammad Agus Kholilurrohman(4)

(1) Universitas Gadjah Mada
(2) Universitas Gadjah Mada
(3) Universitas Gadjah Mada
(4) Universitas Gadjah Mada
(*) Corresponding Author

Abstract


Development is a process of change that is planned to improve various aspects of people’s lives. The development process carried out in Indonesia covers many aspects, one of which is human development. Indicators of the success of a region in the process of developing the quality of human life can be measured using the Human Development Index (HDI). HDI is a number that represents the condition of the population in terms of development, education, health, income, and various other aspects. Human development is important to do in order to achieve the prosperity of a region’s population. Each re gion in Indonesia continues to make various efforts to improve human development, and Java is no exception. To find out what factors affect the Human Development Index on the Java Island, a comparison of Four Mathematical Function Link Models on General ized Linear Models (GLM) is carried out to analyze the factors that affect the Human Development Index. The Four Mathematical Link Function Models are Logit, Probit, Cauchit, and Complementary Log-log (Clog-log) models. The ordinal Probit regression model is the best model to analyze the factors affecting HDI in Java Island in 2023, with classification accuracy of 86.316%.

Keywords


Human Development Index (HDI), Mathematical Link Function Model, Gen eralized Linear Models, Classification

Full Text:

PDF


References

Agresti, A, Categorical Data Analysis. New York: John Wiley and Sons, 1990.

Agresti, A, Categorical Data Analysis. New York: John Wiley and Sons, 2002.

Arafat, L. Rindayati, W. Sahara, Faktor-faktor yang Mempengaruhi Indeks Pembangunan Manusia di Provinsi Kalimantan Tengah. Bogor: Jurnal Ekonomi dan Kebijakan Pembangunan, hlm 140-158, 2018.

BPS, Indeks Pembangunan Manusia. Jakarta : Badan Pusat Statistik, 2008.

BPS, Konsep Indeks Pembangunan Manusia. Jakarta : Badan Pusat Statistik, 2014.

BPS Analisis Kualitas Pembangunan Manusia Provinsi Jawa Tengah 2023. Semarang : Badan Pusat Statistik, 2023.

Felkin, M. Comparing Classification Results between N-ary and Binary Problems. Quality Measures in Data Mining, hlm 277-301, 2007.

Gujarati, D.N, Ekonometrika Dasar : Edisi Keenam. Jakarta: Erlangga, 2003.

HDR, H, Sustaining Human Progress: Reducing Vulnerabilities and Building Resilience. New York: United Nations Development Programme (UNDP), 2014.

Hosmer and Lemeshow, Applied Logistic Regression. New York: John Wiley and Sons, 2000.

Rohmawati, N. M, Analisis Faktor-faktor yang Mempengaruhi Indeks Pembangunan Manusia di Provinsi Jawa Timur (pada 38 Kabupaten/Kota). Malang: FEB UB, 2021.

Witten, I. H., & Frank, E. Data Mining: Practical Machine Learning Tools and Techniques (2nd ed.). 2005.

Haller, G., Chaos Near Resonance, in : Applied Mathematical Sciences, vol 138, Springer, New York, 1999.



DOI: https://doi.org/10.22146/jmt.101505

Article Metrics

Abstract views : 46 | views : 2

Refbacks

  • There are currently no refbacks.



Copyright of Jurnal Matematika Thales ISSN 2715-1891 (Print).

Jumlah Kunjungan: View My Stats


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

JMT Indexed by: