In oman, Fishing is one of the oldest professions that
provides significantly to the national economy and for creating more job
opportunities, especially, where many people completely depend on this income
as an important source of living. The customers dealing with Fish markets in
Oman need a good and innovative software platform to help them to deal with the
problem of increasing of fish prices. This study aims at analysing various
factors behind increasing prices in Oman fish markets using some data mining
algorithms, by means of studying the old data that kept on the database that
will assist to make a proper decision. The research has been conducted for the
data collected from 29 fish markets in Sultanate of Oman and 15 fish species in
each markets have been considered. To analyse the data, data mining algorithms,
namely J48 algorithm, Decision Stump, and Random Tree has been chosen to
perform the classification of data to find the most affected factor in fish
price variations. The suitable algorithm has been chosen based on the good
performance, which has been used for building an application. The result of the
study shows that the Time is the major factor for price variations followed by
Place and then the quantity. This application model will help customers to get
different information about prices in fish markets in Oman.
Oman Fish Market Factor Analyses Attribute Selection Information Gain Weka software Classification algorithm
Primary Language | English |
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Subjects | Computer Software |
Journal Section | Articles |
Authors | |
Publication Date | August 1, 2018 |
Submission Date | June 23, 2018 |
Acceptance Date | August 2, 2018 |
Published in Issue | Year 2018Volume: 1 Issue: 2 |
The papers in this journal are licensed under a Creative Commons Attribution-NonCommercial 4.0 International License