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All Journal Jurnal Riset Pendidikan Matematika AKSIOMA: Jurnal Program Studi Pendidikan Matematika JOIV : International Journal on Informatics Visualization PAEDAGOGIA Abdimas Talenta : Jurnal Pengabdian Kepada Masyarakat Numeracy : Jurnal Ilmiah Pendidikan Matematika BAREKENG: Jurnal Ilmu Matematika dan Terapan JMM (Jurnal Masyarakat Mandiri) JTAM (Jurnal Teori dan Aplikasi Matematika) Wiralodra English Journal (WEJ) JPMI (Jurnal Pendidikan Matematika Indonesia) Gema Wiralodra MES: Journal of Mathematics Education and Science Jurnal Penelitian Pembelajaran Matematika Sekolah Range : Jurnal Pendidikan Matematika Jurnal Sains dan Edukasi Sains Jurnal Anugerah: Jurnal Pengabdian Kepada Masyarakat Bidang Keguruan dan Ilmu Pendidikan Jurnal Penelitian Inovatif MATH-EDU: Jurnal Ilmu Pendidikan Matematika Jurnal Pendidikan dan Pengabdian Masyarakat IndoMath: Indonesia Mathematics Education Indonesian Educational Research Journal Kreativasi: Journal of Community Empowerment Jurnal Jendela Matematika Jurnal Pendidikan MIPA CITAKARYA Jurnal Pengabdian Masyarakat
mone, ferdinandus
Pendidikan Matematika, Universitas Timor
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Journal : Range : Jurnal Pendidikan Matematika

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The Effect of Improving Human Resources for Student Interest in Selecting University on Food Security and Health: Structural Equation Modeling (SEM) Justin Eduardo Simarmata; Ferdinandus Mone; Debora Chrisinta; Winda Ade Fitriya B
RANGE: Jurnal Pendidikan Matematika Vol. 6 No. 1 (2024): Range Juli 2024
Publisher : Pendidikan Matematika UNIMOR

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32938/jpm.v6i1.6308

Abstract

The selection of State Universities by students has a significant impact on improving the quality of human resources, so it can also affect the improvement of food security and health. This study aims to understand the extent of students' interest in selecting university which contributes to improving human resources and can indirectly affect food security and health. This study uses the Structural Equation Modeling (SEM) method to analyze the interaction between latent variables. Data was collected through questionnaires from high school students on the Indonesia-Timor Leste border. The data used in this study include students' interest in selecting university (Y), education and knowledge (X1), skills and abilities (X2), food security (X3), and health (X4). The results showed that students' interest in selecting university had a significant correlation with improving human resources through education by 90% (X1) and 84% (X2). The impact of this increase in human resources is also seen in the improvement of food security and public health which provides a correlation of 98% (X3) and 81% (X4).
Estimation of Path Coefficient Parameter Based on The Best RMSEA Value in Structural Equation Modeling Weighted Least Square Simarmata, Justin Eduardo; Mone, Ferdinandus; Chrisinta , Debora; Purnomo, Miko; Matute, Alejandro Jr. V.
RANGE: Jurnal Pendidikan Matematika Vol. 7 No. 2 (2026): Range Januari 2026
Publisher : Pendidikan Matematika UNIMOR

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32938/jpm.v7i2.10324

Abstract

Structural Equation Modeling (SEM) is a statistical approach widely used to analyze causal relationships between latent and observed variables. A key issue in SEM lies in selecting an appropriate parameter estimation method, as it strongly affects the accuracy and interpretation of results. Among the most common estimation techniques are Maximum Likelihood (ML) and Weighted Least Squares (WLS). This study aims to compare the performance of ML and WLS in estimating path coefficients within SEM analysis. Using simulated data generated with the simulateData() function from a predefined structural model, three scenarios are examined with sample sizes of 500 and 1000. Data transformation procedures are applied to ensure consistency before model testing. Each SEM model is then estimated using both ML and WLS, and the results are evaluated through Root Mean Square Error of Approximation (RMSEA) values obtained from 100 replications. Findings indicate that WLS generally outperforms ML in terms of model fit and stability. In the first scenario with a sample size of 500, WLS achieves a lower average RMSEA (0.0141) compared to ML (0.0172). With a sample size of 1000 in the second scenario, both methods produce similar RMSEA values (0.009 for WLS and 0.0096 for ML), though WLS demonstrates lower variability. In the third scenario, also with a sample size of 1000, WLS records an average RMSEA of 0.0074 versus 0.0092 for ML. Overall, the results suggest that WLS is more effective and reliable than ML in providing accurate parameter estimates across different data conditions and sample sizes.
Co-Authors Agustinus Giovandi Laki Ahzan, Zulkaidah Nur Alfonsa Maria Abi Alfonsa Maria Abi Astriani Dewi, Ni Putu Yuni Bau, Neta Deliana Bete Sanan, Lidia Rosina Bete, Hendrika Bifel, Maria Gabriela Bait Bone, Dominifridus Cecilia Novianti Salsinha Chrisinta, Debora Destiana Ina Elin, Lailin Hijriani Elisabet Ersamayori Foeh Elisabeth E Mayori Garcia-Gracia, Javier Hijriani, Lailin Hijriani, Lailin Intan Karisma, Yunita Jelahu, Ronaldus Ariyanto Juventianus Kenjam Lopo, Angelina Maria Naimnule Maria Pati Kaka Maria Rosalinda Talan Marta Jaha Ghada Martinus Kaka Matheos J Takaeb Matute, Alejandro Jr. V. Merlin Helentina Napitupulu Miko Purnomo Moses Timutang Naimnule, Maria Nampung, Nasrianus Nelciana Talan Oemanas, Hildegardis Kono Oemanas olbata, yabes Paulus Dara Madu Prudensius Manek Putra Kaka Rodríguez-Nieto, Camilo Andrés Ruing, Lusisita Enjelita K Selestina Nahak Siahaan, Meiva M. Lestari Siahaan, Meiva Marthaulina Lestari Sigit, Nanta Silfester Faentaono Simamarta, Justin Eduardo Simarmata, Justin Eduardo Sony Mahardika Stanislaus Amsikan Timutang, Moses Uskono, Yunitha Centriana Valentinus Dendo Winda Ade Fitriya B Wua Laja, Yosepha Patricia yabes olbata Yohanes Jefrianus Kehi Zulkaidah Nur Ahzan Zulkaidah Nur Azhan