MODELING OF FACTORS INFLUENCING GENDER DEVELOPMENT INDEX (GDI) IN PAPUA PROVINCE USING SPLINE NONPARAMETRIC REGRESSION

Sintah Sintah(1), Ferry Kondo Lembang(2), Norisca Lewaherilla(3*)


(1) Statistics Study Program, Department of Statistics, Faculty of Mathematics and Natural Sciences, Pattimura University
(2) Statistics Study Program, Department of Statistics, Faculty of Mathematics and Natural Sciences, Pattimura University
(3) Statistics Study Program, Department of Statistics, Faculty of Mathematics and Natural Sciences, Pattimura University
(*) Corresponding Author

Abstract


The Gender Development Index (GDI) is an index of achieving basic human development capabilities to measure success in efforts to develop the quality of human life by considering gender inequality. Papua Province is the province with the lowest GDI score when compared to the 34 provinces in Indonesia. This condition shows that there is still a development gap between the male and female genders. For this reason, it is necessary to research the factors that are suspected to influence GDI in Papua Province. In this study, the pattern of GDI data and the factors that are thought to influence it do not form a specific pattern, so we used spline nonparametric regression. Based on this study, the best model is obtained by the optimal knot point based on the smallest Generalized Cross Validation (GCV) value, which are 3-knots and six significant variables, namely, Life Expectancy , Expected Years of Schooling , Female Income Contribution , Sex Ratio , Female Labor Force Participation Rate , High School Enrollment Rate. This model has an  of 99.95%. The predictor variable used has an effect of 99.95%, and other variables influence the rest.

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References


S. Aprilianti and Y. Setiadi, “Faktor-faktor Yang Memengaruhi Indeks Pembangunan Gender di Indonesia Tahun 2020,” in Seminar Nasional Official Statistics, 2022, pp. 245–254.

S. U. R. Sari, “Aplikasi Metode Regresi Nonparametrik Spline Multivariabel untuk Pemodelan Faktor-Faktor yang Mempengaruhi Indeks Pembangunan Gender di Provinsi Jawa Barat,” Jurnal Statistika Universitas Muhammadiyah Semarang, vol. 6, no. 2, 2018.

A. Wahyu, L. Firdauzi, T. Waskita, M. Alfana, A. Pitoyo, and Y. Kusmanto, Analisis Indeks Pembangunan Gender Provinsi Maluku Utara. 2020. doi: 10.13140/RG.2.2.11702.52800.

S. Madrim, “Kekerasan Terhadap Perempuan pada Tahun 2021 Merupakan Tertinggi dalam 10 Tahun Terakhir.” Accessed: May 29, 2023. [Online]. Available: Https://Www.Voaindonesia.Com/A/Kekerasan-Terhadap-Perempuan-Pada-2021-Merupakan-Tertinggi-Dalam-10-Tahun-Terakhir-/6473578.Html

Kementerian Pemberdayaan Perempuan dan Perlindungan Anak, “Pembangunan Manusia Berbasis Gender 2021,” 2021.

Z. D. Rizqiana, “Modelling Gender Development Index in Central Java In 2021 with Geographically Weighted Regression,” Journal of Statistical Methods and Data Science, vol. 1, no. 1, pp. 25–36, 2023.

Suparti, R. Santoso, A. Prahutama, and A. R. Devi, Regresi Nonparametrik. Wade Group, 2018.

F. K. Lembang, V. Y. I. Ilwaru, and N. Lewaherilla, “Pemodelan Regresi Nonparametrik Spline dan Aplikasinya Pada Indeks Kebahagiaan Provinsi Di Indonesia,” Jurnal Riset dan Aplikasi Matematika (JRAM), vol. 7, no. 1, pp. 56–65, 2023.

A. Indrasetianingsih, F. Fitriani, and P. J. Kusuma, “Klasifikasi Indeks Pembangunan Gender Di Indonesia Tahun 2020 Menggunakan Supervised Machine Learning Algorithms,” Inferensi, vol. 4, no. 2, pp. 129–136, 2021.

I. Aryantari, “Pemodelan Indeks Pembangunan Gender (IPG) di Provinsi Jawa Timur Menggunakan Regresi Nonparametrik Spline.” Tugas Akhir. Surabaya: Institut Teknologi Sepuluh Nopember, 2017.

R. L. Eubank, Spline Smoothing and Nonparametric Regression. 1988.

G. Wahba, Spline models for observational data. SIAM, 1990.

I. N. Budiantara, “Model Keluarga Spline Polinomial Truncated dalam Regresi Semiparametrik,” Berkala MIPA, vol. 15, no. 3, pp. 55–61, 2005.

D., N. Gurajati, Basic Econometrics, Fourth. Singapore: McGraw-Hill Inc., 2004.

Samin. Radjid, “Pemodelan Prevalensi Balita Stunting Dengan Mengunakan Metode Regresi Nonparametrik Spline (Studi Kasus: Provinsi Maluku, Maluku Utara Dan Papua Tahun 2021),” Skripsi, Universitas Pattimmura, Ambon, 2022.


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DOI: https://doi.org/10.26714/jsunimus.12.2.2024.29-41

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