Deteksi Tingkat Kemiripan Judul Menggunakan Algoritma Oliver Pada Sistem Informasi Pengajuan Skripsi - Nopi Fitrianingsih; Marsani Asfi; Dwi Prasetyo; Ricky Perdana Kusuma; Muhammad Afif Sulhan (Universitas Budi Darma, 2022)
Thesis is the final requirement of academic education. The procedural system for the title checking process is based on the memory of the huma, thus allowing for the similarity of the thesis title. Therefore, a system can detect the degree of similarity of titles automatically in order to prevent redundancy of thesis titles. This study applies the Oliver algorithm which is a function in the PHP programming language that produces a similarity value of two strings. Oliver's algorithm has not been widely applied in plagiarism detection techniques. Oliver algorithm testing using test data as much as 10 test title data and 217 titles for training data. The test results show that Oliver's algorithm produces a percentage of the title similarity level in accordance with the accepted provisions, namely 60%. It was found that 2 out of 10 thesis titles were rejected with a similarity percentage of 70.06% and 62.89% and 8 thesis titles were accepted with a similarity percentage of 31.94%, 30.48%, 26.11%, 31.86%, 29.47%, 31.13%, 35.01% and 37.08%.