Multi-response quality optimization of gluten-free noodles through the integration of taguchi, GRA, and PCA method
DOI:
https://doi.org/10.35194/jmtsi.v10i1.5703Abstract
The demand for gluten-free noodles has steadily increased in response to growing health awareness and dietary needs of individuals with celiac disease or gluten intolerance. A primary challenge in developing gluten-free noodles lies in replicating the viscoelastic properties of gluten to achieve elastic and chewy texture. This study aims to optimize the formulation of gluten-free noodles using a combination of mocaf flour and rice flour through a quality engineering approach by integrating Taguchi Method, Grey Relational Analysis (GRA), and Principal Component Analysis (PCA). The Taguchi method was employed to design experiments involving two main factors—mocaf flour and rice flour—each with three levels. The observed responses were elongation (elasticity) and water absorption. As the study involves multiple quality responses, GRA was used to convert the results into a single value called Grey Relational Grade (GRG), while PCA was applied to determine objective response weights based on eigenvalues derived from the data variables. The experimental results indicated that the optimal combination was achieved with 150 grams of mocaf flour and 50 grams of rice flour (A2B2), with mocaf flour contributing the most to product quality at 71.27%. The integrated methodology effectively identified the optimal parameters without requiring repeated trial-and-error processes and produced consistently high-quality noodles. Statistical assumption tests confirmed that the data were normally distributed and homogeneous, validating the reliability of the ANOVA results. This integrated approach provides a systematic and objective solution to multiresponse optimization in food product development. The study not only contributes to the enhancement of gluten-free noodle quality but also promotes the broader utilization of local ingredients such as mocaf. By adopting this method, producers can efficiently refine their formulations and improve gluten-free product quality, offering a viable alternative to meet the modern market's preferences for gluten-free dietsReferences
[1] B. Lexhaller, M. L. Colgrave, and K. A. Scherf, “Characterization and Relative Quantitation of Wheat, Rye, and Barley Gluten Protein Types by Liquid Chromatography–Tandem Mass Spectrometry,” Front. Plant Sci., vol. 10, no. 2019, 2019, doi: 10.3389/fpls.2019.01530.
[2] A. Diez-Sampedro, M. Olenick, T. Maltseva, and M. Flowers, “A Gluten-Free Diet, Not an Appropriate Choice without a Medical Diagnosis,” J. Nutr. Metab., vol. 2019, 2019, doi: 10.1155/2019/2438934.
[3] H. M. Jaffar, W. Ahsan, and H. N. Koser, “Celiac Disease: An Autoimmune Disorder: Celiac Disease: An Autoimmune Disorder,” Pakistan J. Heal. Sci., p. 2, 2022.
[4] L. Roman, M. Belorio, and M. Gomez, “Gluten?free breads: The gap between research and commercial reality,” Compr. Rev. food Sci. food Saf., vol. 18, no. 3, pp. 690–702, 2019.
[5] H. Toiba, A. Y. M. Noor, M. S. Rahman, R. Hartono, R. Asmara, and D. Retnoningsih, “Consumers’ preference and future consideration toward organic instant noodles: evidence from Indonesia,” Agris on-line Pap. Econ. Informatics, vol. 15, no. 1, pp. 127–137, 2023.
[6] A. Cappelli, N. Oliva, and E. Cini, “A systematic review of gluten-free dough and bread: Dough rheology, bread characteristics, and improvement strategies,” Appl. Sci., vol. 10, no. 18, 2020, doi: 10.3390/APP10186559.
[7] D. K. M. J. Rashid, “Optimize the Taguchi method, the signal-to-noise ratio, and the sensitivity,” Int. J. Stat. Appl. Math., vol. 8, no. 6, pp. 64–70, 2023, doi: 10.22271/maths.2023.v8.i6a.1406.
[8] N. Rahmawati, M. H. Hakim, and R. Akbar, “Peningkatan Kualitas Udang Rebon Kering Multirespon Mengintegrasikan Metode Taguchi Gray Relational Analysis dan Principal Component Analysis,” vol. 4, no. 2, pp. 47–56, 2023.
[9] A. Wulandari, T. Wuryandari, and D. Ispriyanti, “Penerapan Metode Taguchi Untuk Kasus Multirespon Menggunakan Pendekatan Grey Relational Analysis Dan Principal Component Analysis (Studi Kasus Proses Freis Komposit Gfrp),” None, vol. 5, no. 4, pp. 791–800, 2016.
[10] A. Al?Refaie, “Optimizing multiple quality responses in the Taguchi method using fuzzy goal programming: modeling and applications,” Int. J. Intell. Syst., vol. 30, no. 6, pp. 651–675, 2015.
[11] S. B. Sutono, “Grey-based Taguchi Method to Optimize the Multi-response Design of Product Form Design,” J. Optimasi Sist. Ind., vol. 20, no. 2, pp. 136–146, 2021.
[12] N. Jain and R. Kumar, “Multi-response optimization of process parameters in friction stir welded aluminum 6061-T6 alloy using Taguchi grey relational analysis,” World J. Eng., vol. 19, no. 5, pp. 707–716, 2022.
[13] F. Arifin, A. Zamheri, E. S. Martomi, Y. D. Herlambang, A. P. SYAHPUTRA, and I. APRIANSYAH, “Optimization of process parameters in 3D printing FDM by using the Taguchi and Grey relational analysis methods,” J. Ilm. Tek. Mesin, pp. 1–10, 2020.
[14] S. Yuliana, “Analisis Daya Tekan dan Daya Serap Pada Batako Menggunakan Pendekatan Grey Relational Analysis dan Principal Component Analysis,” J. Elektro dan Mesin Terap., vol. 8, no. Vol. 8 No. 2 (2022), pp. 81–90, 2022, doi: 10.35143/elementer.v8i2.5740.
[15] R. Devita, S. Si, and M. Si, “Analisis Variansi Galat Mutlak Data Hasil Pengukuran Arus untuk Beberapa Besaran Tegangan pada Suatu Resistansi,” vol. 1, no. November, pp. 43–52, 2021.
[16] U. Usmadi, “Pengujian Persyaratan Analisis (Uji Homogenitas Dan Uji Normalitas),” Inov. Pendidik., vol. 7, no. 1, pp. 50–62, 2020, doi: 10.31869/ip.v7i1.2281.
[2] A. Diez-Sampedro, M. Olenick, T. Maltseva, and M. Flowers, “A Gluten-Free Diet, Not an Appropriate Choice without a Medical Diagnosis,” J. Nutr. Metab., vol. 2019, 2019, doi: 10.1155/2019/2438934.
[3] H. M. Jaffar, W. Ahsan, and H. N. Koser, “Celiac Disease: An Autoimmune Disorder: Celiac Disease: An Autoimmune Disorder,” Pakistan J. Heal. Sci., p. 2, 2022.
[4] L. Roman, M. Belorio, and M. Gomez, “Gluten?free breads: The gap between research and commercial reality,” Compr. Rev. food Sci. food Saf., vol. 18, no. 3, pp. 690–702, 2019.
[5] H. Toiba, A. Y. M. Noor, M. S. Rahman, R. Hartono, R. Asmara, and D. Retnoningsih, “Consumers’ preference and future consideration toward organic instant noodles: evidence from Indonesia,” Agris on-line Pap. Econ. Informatics, vol. 15, no. 1, pp. 127–137, 2023.
[6] A. Cappelli, N. Oliva, and E. Cini, “A systematic review of gluten-free dough and bread: Dough rheology, bread characteristics, and improvement strategies,” Appl. Sci., vol. 10, no. 18, 2020, doi: 10.3390/APP10186559.
[7] D. K. M. J. Rashid, “Optimize the Taguchi method, the signal-to-noise ratio, and the sensitivity,” Int. J. Stat. Appl. Math., vol. 8, no. 6, pp. 64–70, 2023, doi: 10.22271/maths.2023.v8.i6a.1406.
[8] N. Rahmawati, M. H. Hakim, and R. Akbar, “Peningkatan Kualitas Udang Rebon Kering Multirespon Mengintegrasikan Metode Taguchi Gray Relational Analysis dan Principal Component Analysis,” vol. 4, no. 2, pp. 47–56, 2023.
[9] A. Wulandari, T. Wuryandari, and D. Ispriyanti, “Penerapan Metode Taguchi Untuk Kasus Multirespon Menggunakan Pendekatan Grey Relational Analysis Dan Principal Component Analysis (Studi Kasus Proses Freis Komposit Gfrp),” None, vol. 5, no. 4, pp. 791–800, 2016.
[10] A. Al?Refaie, “Optimizing multiple quality responses in the Taguchi method using fuzzy goal programming: modeling and applications,” Int. J. Intell. Syst., vol. 30, no. 6, pp. 651–675, 2015.
[11] S. B. Sutono, “Grey-based Taguchi Method to Optimize the Multi-response Design of Product Form Design,” J. Optimasi Sist. Ind., vol. 20, no. 2, pp. 136–146, 2021.
[12] N. Jain and R. Kumar, “Multi-response optimization of process parameters in friction stir welded aluminum 6061-T6 alloy using Taguchi grey relational analysis,” World J. Eng., vol. 19, no. 5, pp. 707–716, 2022.
[13] F. Arifin, A. Zamheri, E. S. Martomi, Y. D. Herlambang, A. P. SYAHPUTRA, and I. APRIANSYAH, “Optimization of process parameters in 3D printing FDM by using the Taguchi and Grey relational analysis methods,” J. Ilm. Tek. Mesin, pp. 1–10, 2020.
[14] S. Yuliana, “Analisis Daya Tekan dan Daya Serap Pada Batako Menggunakan Pendekatan Grey Relational Analysis dan Principal Component Analysis,” J. Elektro dan Mesin Terap., vol. 8, no. Vol. 8 No. 2 (2022), pp. 81–90, 2022, doi: 10.35143/elementer.v8i2.5740.
[15] R. Devita, S. Si, and M. Si, “Analisis Variansi Galat Mutlak Data Hasil Pengukuran Arus untuk Beberapa Besaran Tegangan pada Suatu Resistansi,” vol. 1, no. November, pp. 43–52, 2021.
[16] U. Usmadi, “Pengujian Persyaratan Analisis (Uji Homogenitas Dan Uji Normalitas),” Inov. Pendidik., vol. 7, no. 1, pp. 50–62, 2020, doi: 10.31869/ip.v7i1.2281.
Published
2026-03-31
How to Cite
Hakim, M. H. (2026). Multi-response quality optimization of gluten-free noodles through the integration of taguchi, GRA, and PCA method. Jurnal Media Teknik Dan Sistem Industri, 10(1). https://doi.org/10.35194/jmtsi.v10i1.5703
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