Machine Learning Model for Quality Parameters Prediction and Control System Design in the Kecombrang Flower (Etlingera elatior) Extraction Process
Abstract
:1. Introduction
2. Materials and Methods
Machine Learning Model and Control System Design
3. Results and Discussion
3.1. Quality Parameters
3.1.1. Phenols
3.1.2. Flavonoids
3.1.3. pH
3.1.4. Viscosity
3.1.5. Color
3.2. Training of the Machine Learning Model
3.3. Testing of the Machine Learning Model
3.4. Concept of Applying the Model into the Control System
4. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Ardiansyah, A.; Naufalin, R.; Arsil, P.; Latifasari, N.; Wicaksono, R.; Aliim, M.S.; Kartiko, C.; Waluyo, S. Machine Learning Model for Quality Parameters Prediction and Control System Design in the Kecombrang Flower (Etlingera elatior) Extraction Process. Processes 2022, 10, 1341. https://doi.org/10.3390/pr10071341
Ardiansyah A, Naufalin R, Arsil P, Latifasari N, Wicaksono R, Aliim MS, Kartiko C, Waluyo S. Machine Learning Model for Quality Parameters Prediction and Control System Design in the Kecombrang Flower (Etlingera elatior) Extraction Process. Processes. 2022; 10(7):1341. https://doi.org/10.3390/pr10071341
Chicago/Turabian StyleArdiansyah, Ardiansyah, Rifda Naufalin, Poppy Arsil, Nurul Latifasari, Rumpoko Wicaksono, Muhammad Syaiful Aliim, Condro Kartiko, and Sugeng Waluyo. 2022. "Machine Learning Model for Quality Parameters Prediction and Control System Design in the Kecombrang Flower (Etlingera elatior) Extraction Process" Processes 10, no. 7: 1341. https://doi.org/10.3390/pr10071341