Classification of Non-Functional Requirements Using Semantic-FSKNN Based ISO/IEC 9126
Abstract: Non-functional
requirements is one of the important factors that play a role in the success of
software development that is often overlooked by developers, so it cause
adverse effects. In order to obtain the non-functional requirements, it
requires an identification automation system of non-functional requirements.
This research proposes an automation system of identification of non-functional
requirements from the requirement sentence-based classification algorithms of
FSKNN with the addition of semantic factors such as the term development by
hipernim and measurement of semantic relatedness between the term and every
category of quality aspects based ISO / IEC 9126. In the test, the dataset is 1342
sentences from six different datasets. The result of this research is that the
Semantic-FSKNN method can reduce the value of hamming loss or error rate by
21.9%, and also raise the value of accuracy by 43.7%, and also the precision
value amounted to 73.9% compared to FSKNN method without the addition of
semantic factors in it.
Author: Denni Aldi Ramadhani,
Siti Rochimah, Umi Laili Yuhana
Journal Code: jptkomputergg150175
