Research

Research mainly consisted of the following:

•         Studying existing researches and secondary information

This involved studying information on the internet to find out about existing surveys and findings on Mobile banking preferences and questionnaire design.

•    Conducting Focus Group discussions to identify survey questions

Focus group discussions were conducted in groups of 5-6 people in the IIT hostels. Along with this, information from the internet was used to collect the different questions to be included n the questionnaire.

•          Learning WEKA (Waikato Environment for Knowledge Analysis)

WEKA is a data mining/machine learning tool developed by Department of Computer Science, University of Waikato, New Zealand.

The data mining algorithms can either be applied directly to a dataset or called from your own Java code. Weka contains tools for data pre-processing, classification, regression, clustering, association rules, and visualization. It is also well-suited for developing new machine learning schemes.

Weka is open source software issued under the GNU General Public License.

It has three Graphical User Interfaces:

Ø  The Explorer

Ø  The Experimenter

Ø  The Knowledge Flow

The Explorer has the following:

—  Preprocess data

—  Classification

—  Clustering

—  Association Rules

—  Attribute Selection

—  Data Visualization

Preprocess and Cluster Analysis was used to group the students according to their mobile banking preferences.