LINEAR REGRESSION & SUPPORT VECTOR REGRESSION UNTUK PREDIKSI EFFORT PADA PROJEK SCRUM DARI COSMIC FUNCTIONAL SIZE

• NISSA MADANIYAH FADHILAH
• 14002427

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ABSTRAK

 

ABSTRAK Nama : Nissa Madaniyah Fadhilah NIM : 14002427 Program Studi : Ilmu Komputer Jenjang : Strata Dua (S2) Konsentrasi : Software Engineering Judul Thesis : Linear Regression & Support Vector Regression untuk Prediksi Effort pada Projek Scrum dari Cosmic Functional
Size Perubahan yang sering terjadi dalam proyek perangkat lunak dapat memengaruhi keakuratan prediksi effort perangkat lunak dan menghambat kesuksesan mengelola proyek Agile. Survei tentang prediksi perangkat lunak mengungkapkan bahwa hal yang paling berpengaruh pada biaya yang paling umum di antara model estimasi effort adalah ukuran perangkat lunak. Oleh karena itu, sangat penting untuk menjaga manajer tetap mendapat informasi perubahan
software size sehingga upaya peningkatan yang akurat dapat dilakukan. Penelitian ini memiliki tujuan untuk mengamati korelasi antara fitur input yang menggambarkan ukuran COSMIC dari peningkatan dan effort yang diperlukan untuk konteks scrum serta membandingkan dampak metode COSMIC dengan story point pada hasil prediksi. Dataset dari perusahaan industri scrum digunakan untuk training dan testing model prediksi. Algoritma correlation-based
feature selection juga diimplementasikan. Proses selanjutnya adalah melakukan evaluasi menggunakan model Support Vector Regression dan Linear Regression baik menggunakan COSMIC maupun tidak. Hasil menunjukan menggunaan metode COSMIC tidak meningkatkan prediksi effort dalam konteks proyek perangkat lunak Scrum.
Kata kunci: COSMIC functional size measurement, Scrum, Software effort, Support
vector regression (SVR), CFS
 

KATA KUNCI

Linear Regression,SUPPORT VECTOR REGRESSION,Cosmic Functional Size

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DAFTAR PUSTAKA

 

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