CT-GAN UNTUK MENINGKATKAN PERFORMANSI SOFTWARE EFFORT ESTIMATION MODEL

• VENNY YULIANTY
• 14207042

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ABSTRAK

 

ABSTRAK
Nama : Venny Yulianty
NIM : 14207042
Program Studi : Ilmu Komputer
Jenjang : Strata Dua (S2)
Konsentrasi : Software Engineering
Judul Tesis : “CT-GAN untuk Meningkatkan Performansi Software Effort
Estimation Model”
Software effort estimation merupakan bagian penting dari pengembangan perangkat
lunak. Estimasi yang tidak akurat dapat menyebabkan menurunkan kualitas produk.
Software effort estimation mengidentifikasi ukuran, jumlah waktu, upaya kebutuhan
manusia, biaya dan sumber daya lainnya untuk membangun suatu sistem. Metode
machine learning merupakan salah satu metode dalam estimasi perangkat lunak yang
memiliki tingkat keakuratan yang lebih tinggi dibandingkan dengan non machine
learning. Metode dengan machine learning ini akan memberikan hasil yang lebih akurat
jika jumlah data yang digunakan besar. Dataset software effort estimation yang ada
secara publik sebagian besar memiliki jumlah data yang sedikit hingga cenderung
overfit Penelitian ini menerapkan CTGAN untuk mendapatkan data sintetis yang
diketahui dapat mempengaruhi hasil prediksi effort estimation pada model Neural
Network. Prediksi terbaik didapatkan pada dataset desharnais dengan nilai MAE
0.060502, MSE 0.0079659 dan RMSE 0.089252.
Kata kunci :
Software Effort Estimation, Regresi, CTGAN

 

KATA KUNCI

CT-GAN Untuk Meningkatkan Performansi Software

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DAFTAR PUSTAKA

 

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