Analogy-based model for software project effort estimation

International Journal of Advances in Intelligent Informatics

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Title Analogy-based model for software project effort estimation
Creator Ardiansyah, Ardiansyah
Mardhia, Murein Miksa
Handayaningsih, Sri
Subject Analogy estimation; Effort estimation; Software project; Similarity distance; Machine learning
Description Accurate effort estimation of software development plays an important role to predict how much effort should be prepared during the works of a software project so that it can be completed on time and budget. Some sectors, e.g. banking sectors, were renowned fields of software projects, not only due to its huge size of project, but also extremely expensive and takes a long time to completion. Project estimation is essential for software development project able to run on time and budget with maximum quality. This study aims to investigate the accuracy of software project effort estimation with the Analogy method using three parameters: Euclidean, Manhattan and Minkowski distance. Analogy based estimation consists several stage included similarity measure, analogy adaptation, estimation calculation and model evaluation. The results showed that the best combination of Analogy methods was using Manhattan distance with an accuracy of 50% MMRE, 28% MdMRE and Pred(25) 48%. Thus, we can concluded that this model can be used to predict accurately.
Publisher Universitas Ahmad Dahlan
Date 2018-11-11
Type info:eu-repo/semantics/article

Format application/pdf
Source International Journal of Advances in Intelligent Informatics; Vol 4, No 3 (2018): November 2018; 251-260
Language eng

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