Abstract

Most software industries use the Constructive Cost Model (COCOMO) II to estimate the cost of software projects with features that are dependent on the cost drivers. The cost driver's value can influence the project cost estimate accuracy. Nevertheless, the accuracy of the model could be further improved. The difference between the cost estimated by using COCOMO II and the actual project cost is not adequately close. To enhance the accurateness of COCOMO II, an extended method of Gamma Grey Wolf optimization (GWO) is employed for optimization. In our research, the COCOMO II-Extended Gamma GWO produced a higher MMRE value (51.09%) than in models proposed in previous studies, namely COCOMO II-Bee Colony optimization (12.92%), and COCOMO II-GWO (1.110%). This indicates that the proposed strategy of enhancing the model was not able to improve MMRE than original model. This finding could be caused by the additional population, namely Gamma, it not better than the previous populations, namely Alpha, Beta, Delta.

Original languageEnglish
Title of host publication2022 International Seminar on Intelligent Technology and Its Applications
Subtitle of host publicationAdvanced Innovations of Electrical Systems for Humanity, ISITIA 2022 - Proceeding
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages145-150
Number of pages6
ISBN (Electronic)9781665460811
DOIs
Publication statusPublished - 2022
Event23rd International Seminar on Intelligent Technology and Its Applications, ISITIA 2022 - Virtual, Surabaya, Indonesia
Duration: 20 Jul 202221 Jul 2022

Publication series

Name2022 International Seminar on Intelligent Technology and Its Applications: Advanced Innovations of Electrical Systems for Humanity, ISITIA 2022 - Proceeding

Conference

Conference23rd International Seminar on Intelligent Technology and Its Applications, ISITIA 2022
Country/TerritoryIndonesia
CityVirtual, Surabaya
Period20/07/2221/07/22

Keywords

  • COCOMO II
  • MMRE
  • cost
  • effort
  • extended
  • gamma GWO

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