TY - JOUR
T1 - Accuracy improvement of the estimations effort in constructive cost model ii based on logic model of fuzzy
AU - Putri, Rahmi Rizkiana
AU - Sarno, Riyanarto
AU - Siahaan, Daniel
AU - Ahmadiyah, Adhatus Solichah
AU - Rochimah, Siti
N1 - Publisher Copyright:
© 2017 American Scientific Publishers. All rights reserved.
PY - 2017/3
Y1 - 2017/3
N2 - Most of software industry are using Constructive Cost Model (COCOMO) to estimating software cost. COCOMO II has a high dependency on cost drivers, and the role of cost driver assessed to improve the reliability of the estimated effort. COCOMO II is important to be emphasized at uncertainty in the level of input which can generates the uncertainty output and it can leads to the error of estimations. To improve the accuracy of COCOMO II, then it used a trapezoidal membership function of fuzzy logic which is represented by cost driver in COCOMO II. COCOMO II used as the basis of research and used as part of experimental dataset research to describe the approach and compare it with the standard version of COCOMO II. It has been explained that the function of trapezoid can performs better that COCOMO II’s function, because it shows a transition which smooth in the interval, and the final results are not far from the actual effort. From this equation, the value of which is smaller than the MRE or MMRE is closer to the real effort. MMRE of the method which proposed can reduce 16.29% from the previous method.
AB - Most of software industry are using Constructive Cost Model (COCOMO) to estimating software cost. COCOMO II has a high dependency on cost drivers, and the role of cost driver assessed to improve the reliability of the estimated effort. COCOMO II is important to be emphasized at uncertainty in the level of input which can generates the uncertainty output and it can leads to the error of estimations. To improve the accuracy of COCOMO II, then it used a trapezoidal membership function of fuzzy logic which is represented by cost driver in COCOMO II. COCOMO II used as the basis of research and used as part of experimental dataset research to describe the approach and compare it with the standard version of COCOMO II. It has been explained that the function of trapezoid can performs better that COCOMO II’s function, because it shows a transition which smooth in the interval, and the final results are not far from the actual effort. From this equation, the value of which is smaller than the MRE or MMRE is closer to the real effort. MMRE of the method which proposed can reduce 16.29% from the previous method.
KW - COCOMO II
KW - Cost driver
KW - Fuzzy logic
KW - Software cost estimation
KW - Trapezoidal membership function
UR - http://www.scopus.com/inward/record.url?scp=85018618236&partnerID=8YFLogxK
U2 - 10.1166/asl.2017.8767
DO - 10.1166/asl.2017.8767
M3 - Article
AN - SCOPUS:85018618236
SN - 1936-6612
VL - 23
SP - 2478
EP - 2480
JO - Advanced Science Letters
JF - Advanced Science Letters
IS - 3
ER -