Abstract:
Data mining is a process that describes the collection of important information
from a large data. Every day, the movement of the stock curve is listed on the
Indonesia Stock Exchange (IDX). In this paper, using clustering techniques from
fuzzy c-means which is one of the techniques in data mining to group, see the
distribution of data and ideal clusters of composite stock price index (JCI) data.
The fuzzy time series method is also used to predict the movement of the curve in
the next few years. Based on the method used, the results show the variables used
can explain cluster distribution and forecasting by obtaining 3 ideal clusters of
data distribution and down curve on the forecasting results obtained. With the
confidence interval area of 5% and the confidence interval of 10% still allows the
curve to increase at the highest point and experience a decrease in the curve at
the lowest point in the estimated area.
