PERANCANGAN PENGUJIAN PREFERENCE TEST, UJI HEDONIK DAN MUTU HEDONIK MENGGUNAKAN ALGORITMA RADIAL BASIS FUNCTION NETWORK

Authors

  • M. Rizal Permadi Politeknik Negeri Jember
  • Huda Oktafa Politeknik Negeri Jember
  • Khafidurrohman Agustianto Politeknik Negeri Jember

DOI:

https://doi.org/10.31598/sintechjournal.v2i2.282

Keywords:

wheat bread, organoleptic test, machine learning, radial basis function network

Abstract

Wheat Bread producers are required to produce quality products and are liked by consumers. Increasing the quality of bread will certainly have an impact on sales to be generated. One of the efforts in improving the quality is by doing Hedonic test and Hedonic Quality test. This study aims to develop a system capable of providing an assessment of new products to be released on the market. Hedonic quality is used as a variable for assessing bread products with 4 variables, which include flavor, taste, appearance, and texture. While the hedonic test using six classes is very very like, very like, like, rather like, and do not like, then this result will be used as a class of Knowledge Based (KB). This research uses Radial Basis Function Network (RBFN) algorithm, yielding 98,8% accuracy with 10 fold testing technique. The final goal of the development of this system will create a system capable of providing an assessment of a wheat bread product.

Downloads

Download data is not yet available.

References

“Pengujian Organoleptik (Evaluasi Sensori) dalam Industri Pangan,†2006.

W. G. Zhao, C. F. Yu, R. T. Zhan, and R. He, “Research on Data Mining Methods for Organoleptic Determination of Amomum Villosum Product,†2011 IEEE Int. Conf. Bioinforma. Biomed. Work. BIBMW 2011, pp. 873–880, 2011.

R. Gonçalves, J. Hester, N. Carvalho, P. Pinho, and M. Tentzeris, “Passive Sensors for Food Quality Monitoring and Counterfeiting,†Proc. IEEE Sensors, vol. 2014–Decem, no. December, pp. 1511–1514, 2014.

S. Prasarnphanich, A. Pawattana, and P. Chusorn, “Data mining,†Procedia - Social and Behavioral Sciences, vol. 112. pp. 647–651, Sep-2014.

Y. Fan and H. Zhang, “Application of Gabor Filter and Multi-Class SVM in Baking Bread Quality Classification,†2006 IEEE Int. Conf. Mechatronics Autom. ICMA 2006, vol. 2006, pp. 1498–1502, 2006.

P. Goel, “Food Quality Assessment Using Fuzzy Logic,†pp. 1459–1462, 2015.

H. R. Estakhroueiyeh and E. Rashedi, “Detecting Moldy Bread Using An E-Nose and The KNN Classifier,†2015 5th Int. Conf. Comput. Knowl. Eng. ICCKE 2015, pp. 251–255, 2015.

F. Ying and L. Fengquan, “Application of Internet of Things to The Monitoring System for Food Quality Safety,†Proc. - 2013 4th Int. Conf. Digit. Manuf. Autom. ICDMA 2013, pp. 296–298, 2013.

B. Jia and Y. Yang, “The Design of Food Quality Supervision Platform Based on The Internet of Things,†Proc. 2011 Int. Conf. Transp. Mech. Electr. Eng., pp. 263–266, 2011.

I. Concina, M. Falasconi, and V. Sberveglieri, “Electronic Noses as Flexible Tools to Assess Food Quality and Safety: Should We Trust Them?,†IEEE Sens. J., vol. 12, no. 11, pp. 3232–3237, 2012.

H. Ratihwulan, “Karakteristik Sensori Tape Ketan dan Tape Singkong dari Industri Rumah Tangga yang Berbeda di Bogor,†2016.

Sugiyono, Metode Penelitian Kuantitatif, Kualitatif, dan R&D. Bandung: Alfabeta, 2011.

L. S. Hasibuan, C. H. Wijaya, and F. Kusnandar, “Formulation of Papaya Bangkok Puree for Baby with One Fruit Combination Based Sensory Quality,†2010.

C. McCormick, “Radial Basis Function Network (RBFN) Tutorial.†.

T. Xie, H. Yu, and B. Wilamowski, “Comparison between Traditional Neural Networks and Radial Basis Function Networks,†pp. 1194–1199, 2011.

C. McCormick, “Radial Basis Function Network (RBFN) Tutorial.†.

I.B.G Anandita, “Analisis Kinerja Dan Kualitas Hasil Kompresi Pada Citra Medis Sinar X Menggunakan Algoritma Huffman, Lempel Ziv Welch Dan Run Length Encoding", SINTECH.pp 7-15,2018

Downloads

Published

2019-10-28

How to Cite

[1]
M. R. Permadi, Huda Oktafa, and Khafidurrohman Agustianto, “PERANCANGAN PENGUJIAN PREFERENCE TEST, UJI HEDONIK DAN MUTU HEDONIK MENGGUNAKAN ALGORITMA RADIAL BASIS FUNCTION NETWORK”, SINTECH Journal, vol. 2, no. 2, pp. 98-107, Oct. 2019.