Article Per Year (5 Year)
p-Index From 2020 - 2025
0
P-Index
This Author published in this journals
All Journal TELKOMNIKA (Telecommunication Computing Electronics and Control)
Kholed Langsari
Fatoni University
Computer Science & IT

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
Optimizing Time and Effort Parameters of COCOMO II using Fuzzy Multi-Objective Particle Swarm Optimization Kholed Langsari; Riyanarto Sarno; Sholiq Sholiq
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 16, No 5: October 2018
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v16i5.9698

Abstract

Estimating the efforts, costs, and schedules of software projects is a frequent challenge to software development projects. A bad estimation will result in bad management of a project. Various models of estimation have been defined to complete this estimate. The Constructive Cost Model II (COCOMO II) is one of the most famous models as a model for estimating efforts, costs, and schedules. To estimate the effort, cost, and schedule in project of software, the COCOMO II uses inputs: Effort Multiplier (EM), Scale Factor (SF), and Source Line of Code (SLOC). Evidently, this model is still lack in terms of accuracy rates in both efforts estimated and time of development. In this paper, we introduced to use Gaussian Membership Function (GMF) of Fuzzy Logic and Multi-Objective Particle Swarm Optimization (MOPSO) method to calibrate and optimize the parameters of COCOMO II. It is to achieve a new level of accuracy better on COCOMO II. The Nasa93 dataset is used to implement the method proposed. The experimental results of the method proposed have reduced the error downto 11.89% and 8.08% compared to the original COCOMO II. This method proposed has achieved better results than previous studies.
Optimizing Effort Parameter of COCOMO II Using Particle Swarm Optimization Method Kholed Langsari; Riyanarto Sarno; Sholiq Sholiq
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 16, No 5: October 2018
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v16i5.9703

Abstract

Estimating the effort and cost of software is an important activity for software project managers. A poor estimate (overestimates or underestimates) will result in poor software project management. To handle this problem, many researchers have proposed various models for estimating software cost. Constructive Cost Model II (COCOMO II) is one of the best known and widely used models for estimating software costs. To estimate the cost of a software project, the COCOMO II model uses software size, cost drivers, scale factors as inputs. However, this model is still lacking in terms of accuracy. To improve the accuracy of COCOMO II model, this study examines the effect of the cost factor and scale factor in improving the accuracy of effort estimation. In this study, we initialized using Particle Swarm Optimization (PSO) to optimize the parameters in a model of COCOMO II. The method proposed is implemented using the Turkish Software Industry dataset which has 12 data items. The method can handle improper and uncertain inputs efficiently, as well as improves the reliability of software effort. The experiment results by MMRE were 34.1939%, indicating better high accuracy and significantly minimizing error 698.9461% and 104.876%.
Co-Authors Riyanarto Sarno Sholiq