How Can IPMA Analysis Through PLS-SEM Identify Maternal Health Risk Factors?
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Abstract
This quantitative study explores maternal health risk factors through Partial Least Squares Structural Equation Modeling (PLS-SEM), employing a cross-sectional design. The dataset, sourced from Kaggle, includes variables such as age, blood pressure, blood sugar, body temperature, and heart rate. Using SmartPLS version 4, the research integrates both exploratory and confirmatory approaches to identify significant predictors of maternal health risks. Importance-Performance Map Analysis (IPMA) highlights that blood sugar (path coefficient = 0.465) and systolic blood pressure (0.274) are the most critical factors. These findings suggest that managing blood sugar and blood pressure should be prioritised in maternal health interventions. Future studies should focus on predictive algorithms and refining sensor-based monitoring systems for real-time assessment.
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References
Al Hakim, R. R. (2022). Perilaku Harian dan Profil Demografi Mempengaruhi Kenaikan Tagihan Listrik Selama Covid-19 di Indonesia: Pendekatan SEM-PLS. AKUA: Jurnal Akuntasi Dan Keuangan, 1(1), 68–76. https://doi.org/10.54259/akua.v1i1.217
Al Hakim, R. R., & Hidayah, H. A. (2022). Pendekatan Structural Equation Modeling untuk Penelitian Pendidikan. Sintesa: Jurnal Ilmu Pendidikan, 17(1), 1–7.
Andayani, Q., Koesbardiati, T., Sujoso, A. D., Masruroh, & Laksono, A. D. (2021). The Barrier to Access Health Insurance for Maternity Care: Case Study of Female Workers in Indonesia. Medico-Legal Update, 21(2), 926–932.
Awang, Z., Afthanorhan, A., & Asri, M. A. M. (2015). Parametric and Non Parametric Approach in Structural Equation Modeling (SEM): The Application of Bootstrapping. Modern Applied Science, 9(9), 58–67. https://doi.org/10.5539/mas.v9n9p58
Cakir, F. S. (2019). Partial Least Squares Structural Equation Modeling (PLS-SEM) and an Application. Journal of Social Research and Behavioral Sciences, 5(9), 111–128.
Hair, J. F., Ringle, C. M., & Sarstedt, M. (2012). Partial Least Squares: The Better Approach to Structural Equation Modeling? Long Range Planning, 45, 312–319. https://doi.org/10.1016/j.lrp.2012.09.011
Hair, J. F., Sarstedt, M., Ringle, C. M., & Gudergan, S. P. (2019). Advanced Issues in Partial Least Squares Structural Equation Modeling (Issue 1).
Larasakti, A. N., & Suyani, S. (2023). The Relationship of Mother’s Age and Parity with Incident of Hypertension in Pregnancy at RSUD Muntilan. Menara Journal of Health Science, 2(4), 723–733.
Munawaroh, Ratama, N., Rasapta, D., Septa, Syty, S. Q., & Purnama, O. A. A. (2022). Implementation of an Expert System in Diagnosing Obstetrical Health in Pregnant Women using Fuzzy Algorithms and Certainty Factor. 2022 IEEE 8th International Conference on Computing, Engineering and Design (ICCED), 1–6. https://doi.org/10.1109/ICCED56140.2022.10010502
Paydar, K., Niakan Kalhori, S. R., Akbarian, M., & Sheikhtaheri, A. (2017). A clinical decision support system for prediction of pregnancy outcome in pregnant women with systemic lupus erythematosus. International Journal of Medical Informatics, 97, 239–246. https://doi.org/10.1016/J.IJMEDINF.2016.10.018
R Core Team. (2016). R: A language and environment for statistical computing [Computer software manual].
Ringle, C. M., Wende, S., & Becker, J.-M. (2024). SmartPLS 4. SmartPLS. https://www.smartpls.com/
Sarstedt, M., Ringle, C. M., & Hair, J. F. (2017). Partial Least Squares Structural Equation Modeling. In Handbook of Market Research. Springer International Publishing AG. https://doi.org/10.1007/978-3-319-05542-8_15-1
Soelaiman, N. F., Ahmad, S. S. S., Mohd, O., Al Hakim, R. R., & Hidayah, H. A. (2022). Modeling the civil servant discipline in Indonesia: partial least square-structural equation modeling approach. Asean International Journal of Business, 1(1), 43–58. https://doi.org/10.54099/aijb.v1i1.72
Soelaiman, N. F., & Al-Hakim, R. R. (2022). Pelanggaran Kedisiplinan yang Kerap Dilakukan Pegawai Negeri Sipil di Lingkungan Politeknik Negeri: Analisis Regresi Linear Terhadap Faktor-faktornya. Prosiding Seminar Nasional Humaniora, 2, 20–24. https://www.conference.unja.ac.id/SNH/article/view/192
Teeluckdharry, N. B., Teeroovengadum, V., & Seebaluck, A. K. (2022). A roadmap for the application of PLS-SEM and IPMA for effective service quality improvements. TQM Journal, 1754–2731. https://doi.org/10.1108/TQM-11-2021-0340
Tohari, A. (2018). Pemodelan Derajat Kesehatan Menggunakan Structural Equation Modeling di Kabupaten Kediri. J Statistika: Jurnal Ilmiah Teori Dan Aplikasi Statistika, 10(2). https://doi.org/10.36456/JSTAT.VOL10.NO2.A1022
Wahyuhidaya, P., & Apriliani, D. (2023). The Relationship Between Maternal Characteristics and The Incidence of Low Birth Weight Babies in The Sleman Health Center Work Area. Menara Journal of Health Science, 2(4), 515–526.