Abstract:
Data mining is seen as an increasingly
important tool by modern business to transform
data into an informational advantage. Data mining
could also be described as trying to create a
simplified model of the complex world described in
the database. Data mining is a way of dealing with
large amounts of information, and it is helpful for
finding useful information faster than any human.
Decision tree is mainly used for classification
purposes. Decision tree is a classifier in the form of
a tree structure. Rules can be easily extracted from
the decision tree. The main task performed in this
system is using inductive methods to the given
values of attributes of an unknown object to
determine appropriate classification according to
decision tree rules. This paper examines the
decision tree learning algorithm for classifying job
related accounting field. This paper implements the
decision tree using ID3 and gives advice to users
about the types of job in accounting field. This
system uses 900 training data set and 300 testing
data set. This paper calculates the system accuracy
by using Hold_Out Method and provides 84.75%
after reviewing 300 testing data set.
