TY - GEN
T1 - Improving the Accuracy of COCOMO II Using Extended Gamma GWO
AU - Putri, Rahmi Rizkiana
AU - Siahaan, Daniel
AU - Fatichah, Chastine
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - 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.
AB - 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.
KW - COCOMO II
KW - MMRE
KW - cost
KW - effort
KW - extended
KW - gamma GWO
UR - http://www.scopus.com/inward/record.url?scp=85137944761&partnerID=8YFLogxK
U2 - 10.1109/ISITIA56226.2022.9855265
DO - 10.1109/ISITIA56226.2022.9855265
M3 - Conference contribution
AN - SCOPUS:85137944761
T3 - 2022 International Seminar on Intelligent Technology and Its Applications: Advanced Innovations of Electrical Systems for Humanity, ISITIA 2022 - Proceeding
SP - 145
EP - 150
BT - 2022 International Seminar on Intelligent Technology and Its Applications
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 23rd International Seminar on Intelligent Technology and Its Applications, ISITIA 2022
Y2 - 20 July 2022 through 21 July 2022
ER -