Journal of Data Science and Software Engineering
Vol 1 No 01 (2020)

PENGARUH SOFTWARE METRIK PADA KINERJA KLASIFIKASI CACAT SOFTWARE DENGAN ANN

Achmad Zainudin Nur (ULM)
Mohammad Reza Faisal (Unknown)
Friska Abadi (Unknown)
Irwan Budiman (Unknown)
Rudy Herteno (Unknown)



Article Info

Publish Date
29 Jun 2020

Abstract

Software Defect Prediction has an important role in quality software. This study uses 12 D datasets from NASA MDP which then features a selection of metrics categories software. Feature selection is performed to find out metrics software which are influential in predicting defects software. After the feature selection of the metric software category, classification will be performed using the algorithm Artificial Neural Network and validated with 5-Fold Cross Validation. Then conducted an evaluation with Area Under Curve (AUC), From datasets D” 12 NASA MDP that were evaluated with AUC, PC4, PC1 and PC3 datasets obtained the best AUC performance values. Each value is 0.915, 0.828, and 0.826 using the algorithm Artificial Neural Network.

Copyrights © 2020






Journal Info

Abbrev

integer

Publisher

Subject

Computer Science & IT

Description

Journal of Data Science and Software Engineering adalah jurnal yang dikelola oleh program studi Ilmu Komputer Universitas Lambung Mangkurat untuk mempublikasikan artikel ilmiah mahasiswa tugas akhir. Terbit tiga kali dalam ...