(Universitas Ahmad Dahlan, Indonesia)(2) Murein Miksa Mardhia
(Universitas Ahmad Dahlan, Indonesia)(3) Sri Handayaningsih
(Universitas Ahmad Dahlan, Indonesia)*corresponding author
AbstractAccurate 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.
KeywordsAnalogy estimation; Effort estimation; Software project; Similarity distance; Machine learning
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DOIhttps://doi.org/10.26555/ijain.v4i3.266 |
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