MODELLING INGREDIENT OF JAMU TO PREDICT ITS EFFICACY

Farit Mochamad Afendi (Graduate School of Information Science, Nara Institute of Science and Technology, Nara, Japan and Department of Statistics, Bogor Agricultural University, Bogor, Indonesia)
Sulistiyani . (Biopharmaca Research Center, Bogor Agricultural University, Bogor, Indonesia)
Aki Hirai (Graduate School of Information Science, Nara Institute of Science and Technology, Nara, Japan)
Md. Altaf-Ul-Amin . (Graduate School of Information Science, Nara Institute of Science and Technology, Nara, Japan)
Hiroki Takahashi (Graduate School of Information Science, Nara Institute of Science and Technology, Nara, Japan)
Kensuke Nakamura (Graduate School of Information Science, Nara Institute of Science and Technology, Nara, Japan)
Shigehiko Kanaya (Graduate School of Information Science, Nara Institute of Science and Technology, Nara, Japan)

FORUM STATISTIKA DAN KOMPUTASI
Vol. 15 No. 2 (2010)

Jamu is an Indonesian herbal medicine made from a mixture of several plants.  Nowadays, many jamu are  produced commercially by many industries in Indonesia.  Each producer may have their own jamu formula. However, one is certain; the efficacy of jamu is determined by the composition of the plants used.  Thus, it is interesting to model the ingredient of jamu which consist of plants and use it to predict efficacy of jamu.  In this analysis, Partial Least Squares Discriminant Analysis (PLSDA) is used in modeling jamu ingredients to predict  the  efficacy.  It  is  obtained  that  utilizing the prediction of  y ij obtained  from  PLSDA  directly  rather  than  use  it  to calculate probability of jamu i belong to efficacy j and then use the probability to predict efficacy produces lower False Positive Rate (FPR) in predicting efficacy group.  Keywords: Jamu, PLSDA