Pemdelan Fuzzy untuk Data Time Series Menggunakan Metode Tabel Look Up dengan Transformasi Logaritma dan Diferensi dan Aplikasinya pada Data Indeks Harga Saham Gabungan (IHSG) - Hari Purnomo (LPPM Press, 2013)
The purpose of this study is to form a fuzzy model for data time series using a lookup table withlogarithmic transformation and differentiation as well as its application to predict IHSG listed on theBSE. First, all data of IHSG is made in logarithm and differentiation. Then, the formation of the fuzzyrules is by lookup table. In this study, the prediction of IHSG is only based on time series data of IHSGwith 144 data as the training data. The results of this study are the prediction of IHSG is based on 6 fuzzymodels formed to conclude that the model of fuzzy lookup table 8 input with logarithmic transformation isthe best model to predict IHSG. It can be seen from MAPE produced by the model is 4.09%. When it iscompared to fuzzy model 8 inputs without transformation in preceding studies, fuzzy models 8 inputs withlogarithmic transformation is still a better model because it has a smaller MAPE values.