Peningkatan Akurasi Estimasi Usaha dan Biaya COCOMO II Berdasarkan Gaussian dan BCO

Autor:	Daniel Siahaan, Rahmi Rizkiana Putri, Sarwosri Sarwosri
Rok vydání:	2017
Předmět:	Estimation Engineering Software Cost estimate business.industry COCOMO Cost driver Process (computing) Artificial intelligence Project management business Fuzzy logic Reliability engineering
Zdroj:	Jurnal Nasional Teknik Elektro dan Teknologi Informasi (JNTETI). 6
ISSN:	2460-5719 2301-4156
DOI:	10.22146/jnteti.v6i3.333
Popis:	An accurate effort and cost estimation provides good management for software projects. Less accurate estimation will affect the management of the software project and cause the ineffectiveness of the project development process. The addition of cost driver, introduced by Barry Boehm in 2000, is used in this paper to provide better accuracy, because it has covered the entire section in the estimation. However, in this paper, the accuracy of effort and cost estimation by COCOMO II Fuzzy Gaussian method is still far from actual effort. Therefore, the accuracy can still be increased using Bee Colony Optimization (BCO), as seen in the MMRE loyal results. The value of parameter A and B on COCOMO II is also changed with the initial gradual of 0.01 to give optimal value on a certain gradual. Based on the result of the implementation, the error accuracy of effort estimation and software project cost is reduced by 38%, compared to previous research. In conclusion, the proposed method can increase the accuracy of effort and cost estimation.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::3f0f3901157c3a5e2b017b7afa2a755d https://doi.org/10.22146/jnteti.v6i3.333 Zobrazit plný text záznamu