PROVINCIAL SEGMENTATION IN INDONESIA: EXPLORING FACTORS INFLUENCING EDUCATION WITH SEM-PLS METHOD, INCORPORATING MODERATION EFFECTS AND FIMIX-PLS APPROACH

  • Davina Shafa Vanisa Department of Mathematics, Faculty of Science and Technology, Universitas Airlangga, Indonesia
  • Tentri Ryan Rahmanita Department of Mathematics, Faculty of Science and Technology, Universitas Airlangga, Indonesia
  • Elly Ana Department of Mathematics, Faculty of Science and Technology, Universitas Airlangga, Indonesia https://orcid.org/0009-0000-6254-3447
  • Ardi Kurniawan Department of Mathematics, Faculty of Science and Technology, Universitas Airlangga, Indonesia
Keywords: Provincial Segmentation, FIMIX-PLS, Moderation, Indonesian Education

Abstract

The significance of education as a developmental metric is underscored by its designation as the 4th goal in the SDGs, which emphasizes ensuring inclusive, equitable, and high-quality education while also expanding lifelong learning opportunities for all. This research relies on two primary sources: secondary data from publications by the Indonesian Central Statistics Agency (BPS RI) in 2023 and the BPS website. The educational variables examined in this study are believed to be influenced by latent variables, including school performance, infrastructure, and poverty levels. Employing the Finite Mixture Partial Least Squares (FIMIX-PLS) approach, the research identified 13 valid and reliable indicators of educational variables. It delineated three regional groups based on the lowest BIC and CAIC values. In this structural equation research, the moderation effect is seen in the significance of the indirect relationship, especially the influence of Regional Poverty on Education with School Outcomes as a moderating construct.

Downloads

Download data is not yet available.

References

M. R. Putri, G. S. Nugraha, and R. Dwiyansaputra, “Pengelompokan Provinsi di Indonesia Berdasarkan Indikator Pendidikan Menggunakan Metode K-Means Clustering,” Journal of Computer Science and Informatics Engineering (J-Cosine), vol. 7, no. 1, pp. 76–83, 2023.

M. Saini, E. Sengupta, M. Singh, H. Singh, and J. Singh, “Sustainable Development Goal for Quality Education (SDG 4): A study on SDG 4 to extract the pattern of association among the indicators of SDG 4 employing a genetic algorithm,” Educ Inf Technol (Dordr), vol. 28, no. 2, pp. 2031–2069, 2023.

Bappenas, “Pendidikan Berkualitas,” Bappenas. Accessed: Feb. 06, 2024. [Online]. Available: https://sdgs.bappenas.go.id/17-goals/goal-4/

R. Bali Swain and F. Yang-Wallentin, “Achieving sustainable development goals: predicaments and strategies,” International Journal of Sustainable Development & World Ecology, vol. 27, no. 2, pp. 96–106, 2020.

H. Wiratama, “Analisis Persebaran dan Ketersediaan Sekolah Menengah Di Kota Tanjungbalai Tahun 2014,” 2015.

C. F. Ramadani, “Penerapan K-Medoids dalam Penggerombolan Provinsi di Indonesia berdasarkan Indikator Pendidikan Jenjang SMA”.

M. S. Putri, “Perbandingan Metode K-Means dan AG K-Means dalam Penggerombolan Provinsi di Indonesia Berdasarkan Indikator Pendidikan”.

W. I. Putri, “Analisis Terhadap Indikator–Indikator yang Mencirikan Standar Nasional Pendidikan Sekolah Menengah Pertama di Indonesia”.

E. D. Anggita, A. Hoyyi, and A. Rusgiyono, “Analisis Structural Equation Modelling Pendekatan Partial Least Square dan Pengelompokan dengan Finite Mixture PLS (FIMIX-PLS)(Studi Kasus: Kemiskinan Rumah Tangga di Indonesia 2017),” Jurnal Gaussian, vol. 8, no. 1, pp. 35–45, 2019.

I. Ghozali, “Structural Equation Modelling Metode Alternatif dengan Partial Least Square Semarang,” Universitas Diponegoro, 2011.

C. Hahn, M. D. Johnson, A. Herrmann, and F. Huber, “Capturing customer heterogeneity using a finite mixture PLS approach,” Schmalenbach Business Review, vol. 54, pp. 243–269, 2002.

J. F. Hair, M. Sarstedt, and C. M. Ringle, “Rethinking some of the rethinking of partial least squares,” Eur J Mark, vol. 53, no. 4, pp. 566–584, 2019.

T. Nur, “Pengaruh growth opportunity, profitabilitas dan struktur modal terhadap nilai perusahaan dengan dividen sebagai variabel intervening pada perusahaan manufaktur yang terdaftar di BEI pada periode 2014-2017,” Jurnal Manajemen Dan Bisnis Indonesia, vol. 5, no. 3, pp. 393–411, 2018.

L. K. Harahap and M. Pd, “Analisis SEM (Structural Equation Modelling) dengan SMARTPLS (partial least square),” Fakultas Sains Dan Teknologi Uin Walisongo Semarang, vol. 1, no. 1, pp. 1–11, 2020.

E. R. CHAIRANI, “Analisis Faktor Penentu Keputusan Konsumen Dalam Pembelian Produk Kecantikan Halal Dengan Metode Analisis Structural Equation Modeling-Partial Least Square (Sem-Pls),” 2022.

J. F. Hair, C. M. Ringle, M. Sarstedt, and G. , T. M. Hult, A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM), vol. 3. Sage Publishing, 2021.

A. Ramirez-Orellana, M. del Carmen Valls Martinez, and M. S. Grasso, “Using higher-order constructs to estimate health-disease status: the effect of health system performance and sustainability,” Mathematics, vol. 9, no. 11, p. 1228, 2021.

J. Henseler, C. M. Ringle, and R. R. Sinkovics, “The use of partial least squares path modeling in international marketing,” in New challenges to international marketing, vol. 20, Emerald Group Publishing Limited, 2009, pp. 277–319.

M. Sarstedt, J.-M. Becker, C. M. Ringle, and M. Schwaiger, “Uncovering and treating unobserved heterogeneity with FIMIX-PLS: which model selection criterion provides an appropriate number of segments?,” Schmalenbach Business Review, vol. 63, pp. 34–62, 2011.

E. E. Rigdon, C. M. Ringle, and M. Sarstedt, “Structural modeling of heterogeneous data with partial least squares,” Review of marketing research, pp. 255–296, 2010.

B. W. Otok, R. Sriningsih, and D. S. Dila, “Segmentation of toddler nutritional status using REBUS and FIMIX partial least square in Southeast Sulawesi,” MethodsX, vol. 12, p. 102515, 2024.

Sugiyono, “Statistika untuk Penlitian,” Alfa Beta, 2019.

Published
2024-07-31
How to Cite
[1]
D. Vanisa, T. Rahmanita, E. Ana, and A. Kurniawan, “PROVINCIAL SEGMENTATION IN INDONESIA: EXPLORING FACTORS INFLUENCING EDUCATION WITH SEM-PLS METHOD, INCORPORATING MODERATION EFFECTS AND FIMIX-PLS APPROACH”, BAREKENG: J. Math. & App., vol. 18, no. 3, pp. 1955-1962, Jul. 2024.