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Efficacy Prediction of Jamu Formulations by PLS Modeling

2013; Bentham Science Publishers; Volume: 9; Issue: 1 Linguagem: Inglês

10.2174/1573409911309010005

1875-6697

Farit Mochamad Afendi, Latifah Kosim Darusman, Aki Morita, Md. Altaf‐Ul‐Amin, Hiroki Takahashi, Kensuke Nakamura, Ken Tanaka, Shigehiko Kanaya,

Spectroscopy and Chemometric Analyses

Indonesian herbal medicines made from mixtures of several plants are called “Jamu.” The efficacy of a particular Jamu is determined by its ingredients i.e. the composition of the plants. Thus, we modeled the ingredients of Jamu formulas using Partial Least Squares Discriminant Analysis (PLS-DA) in order to predict their efficacy. The plants used in each Jamu medicine served as the predictors, whereas the efficacy of each Jamu provided the responses. Utilizing response predictions obtained from PLS-DA, we predicted the efficacies of Jamu formulations using two methods: maximum response prediction and maximum probability. In predictions of Jamu efficacy, the maximum response prediction method produced a smaller error than that the maximum probability method. Furthermore, utilizing the PLSDA coefficient matrix, we determined the efficacy for which a plant is most useful, based on its largest coefficients. Keywords: Efficacy, Jamu, main ingredients, medicinal plant, multivariate analysis, PLS-DA, regression coefficient, response prediction, formulation, modelling