Prediksi Time Effort Pengembangan Perangkat Lunak Agile menggunakan Teknik Machine Learning

• MUCHAMAD BACHRAM SHIDIQ
• 14210136

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ABSTRAK

ABSTRAK

Nama                   : Muchamad Bachram Shidiq

NIM                      : 14210136

Program Studi      : Ilmu Komputer

Fakultas               : Teknologi Informasi

Jenjang                : Strata Dua (S2)

Konsentrasi          : Software Engineering

Judul         : “Prediksi Time Effort Pengembangan Perangkat Lunak Agile menggunakan Teknik Machine Learning”

Dalam rangka menjalankan proyek pengembangan perangkat lunak, diperlukan mekanisme pengelolaan atau manajemen proyek yang efektif dan efisien untuk mengkoordinasikan kegiatan yang dilakukan. Metode agile dikembangkan karena terdapat beberapa kelemahan pada metode klasik yang dapat mengganggu jalannya proses pengembangan perangkat lunak sesuai keinginan pengguna. Namun dalam penerapan metode agile, belum dapat dilakukan time effort estimation dengan baik. Hal ini dapat menyebabkan project manager kesulitan menyiapkan sumber daya dalam pengembangan perangkat lunak pada scrum project. Planning poker sebagai salah satu metode populer untuk effort estimation agile-scrum project, namun planning poker memiliki kerentanan terhadap masalah bias, dinamika tim, dan boros waktu. Untuk itu penelitian ini bertujuan melakukan prediksi time effort pengembangan perangkat lunak agile menggunakan teknik Machine Learning yaitu algoritma Decision Tree, Random Forest, Gradient Boosting, dan AdaBoost, serta penggunaan feature selection berupa RRelieff dan Principal Component Analysis (PCA) untuk peningkatan akurasi prediksi.

KATA KUNCI

Agile,machine learning,Decision Tree,Random Forest,Gradient Boosting

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