<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>In developing optimal entrepreneurship, several variables such as motivation, knowledge, intensity, and capacity are required to determine their relationship using the Partial Least Square-Structural Equation Modeling (PLS-SEM). The results show that entrepreneurial motivation and knowledge significantly affect intensity. Also, motivation and intensity significantly influenced capacity. The parameter estimator of PLS-SEM can be improved by applying hybridization to the Artificial Neural Network (PLS-ANN) using the 2:32:8:1 architecture in which motivation and intensity were the input while capacity was the output. The comparison parameter accuracy model measured by MSE, RMSE, and MAE shows the improvement accuracy by PLS-ANN better than PLS-SEM.</p>
</abstract>

In developing optimal entrepreneurship, several variables such as motivation, knowledge, intensity, and capacity are required to determine their relationship using the Partial Least Square-Structural Equation Modeling (PLS-SEM). The results show that entrepreneurial motivation and knowledge significantly affect intensity. Also, motivation and intensity significantly influenced capacity. The parameter estimator of PLS-SEM can be improved by applying hybridization to the Artificial Neural Network (PLS-ANN) using the 2:32:8:1 architecture in which motivation and intensity were the input while capacity was the output. The comparison parameter accuracy model measured by MSE, RMSE, and MAE shows the improvement accuracy by PLS-ANN better than PLS-SEM.

An Improvement of Parameter Estimation Accuracy of Structural Equation Modeling using Hybridization of Artificial Neural Network in the Entrepreneurship Structural Model

Department of Mathematics and Data Science, Faculty of Mathematics and Natural Sciences

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

In developing optimal entrepreneurship, several variables such as motivation, knowledge, intensity, and capacity are required to determine their relationship...

An Improvement of Parameter Estimation Accuracy of Structural Equation Modeling using Hybridization of Artificial Neural Network in the Entrepreneurship Structural Model

Publié en ligne: 16 juin 2023

Pages: 2279 - 2302

Reçu: 08 août 2022

Accepté: 19 déc. 2022

DOI: https://doi.org/10.2478/amns.2023.1.00411

Mots clés
PLS-SEM, ANN, PLS-ANN, Hybrid model, Entrepreneurship AMS

© 2023 Dodi Devianto et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

An Improvement of Parameter Estimation Accuracy of Structural Equation Modeling using Hybridization of Artificial Neural Network in the Entrepreneurship Structural Model

Publié en ligne: 16 juin 2023

Pages: 2279 - 2302

Reçu: 08 août 2022

Accepté: 19 déc. 2022

DOI: https://doi.org/10.2478/amns.2023.1.00411

Mots clésPLS-SEM, ANN, PLS-ANN, Hybrid model, Entrepreneurship AMS

© 2023 Dodi Devianto et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Mots clés
PLS-SEM, ANN, PLS-ANN, Hybrid model, Entrepreneurship AMS