<> "The repository administrator has not yet configured an RDF license."^^ . <> . . . "Student Final Project Topic Classification System Using the\r\nXGBoost Algorithm"^^ . "Student Final Project Topic Classification System Using the\r\nXGBoost Algorithm\r\nNabila Rasman Sutandi1\r\n, Boldson Herdianto Situmorang2\r\n, Dinar Munggaran Akhmad3*\r\n1,2,3 Department of Computer Science, Faculty of Mathematics and Natural Science, Pakuan\r\nUniversity, Bogor, West Java, 16143, Indonesia\r\nAbstract\r\nThe final project is one of the requirements that must be met by students to complete their education in\r\nhigher education. The data on the title of the final project of the students of the Computer Science Study\r\nProgram at Pakuan University is still being recorded based on the student graduation period and has not been\r\nclassified based on the topic of the final project, so that students who will carry out the final project have\r\ndifficulty finding references for the title of the final project that suits the topic. This research aims to create a\r\nclassification system for student final project topics using the Extreme Gradient Boosting (XGBoost)\r\nalgorithm. The development of the system is assisted by the Term Frequency-Inverse Document Frequency\r\n(TF-IDF) method and is classified into 4 topics, namely Artificial Intelligence, Hardware Programming,\r\nComputer Networking, and Software Engineering. This study used 1079 final project title data from 2018-\r\n2022, which was divided into 3 comparisons of training data and test data, namely 70:30 (model 1), 80:20\r\n(model 2), and 90:10 (model 3). Parameter tuning is carried out using gridsearchCV and k-fold cross validation\r\nto get the best parameters. The results showed that model 3 had the best performance with an accuracy of\r\n87.85%. The XGBoost model in the system automatically predicts the title of the final project along with its\r\ntopic label, so admins don't need to add topics manually. Users (students) can view and search for final project\r\ntitle data based on topics that have been classified to be used as a reference for new final project titles according\r\nto the topic.\r\nKeywords: Final Project Topic; Classification; System; XGBoost; TF-IDF"^^ . "2024-08-09" . . . "Universitas Pakuan"^^ . . . "Fakultas Matematika dan Pengetahuan Alam, Universitas Pakuan"^^ . . . . . . . . . . . . . . . . . . "Dinar"^^ . "Munggaran Akmad"^^ . "Dinar Munggaran Akmad"^^ . . ""^^ . ""^^ . " "^^ . . "Nabila Rasman"^^ . "Sutandi"^^ . "Nabila Rasman Sutandi"^^ . . "Boldson"^^ . "Herdianto Situmorang"^^ . "Boldson Herdianto Situmorang"^^ . . "Universitas Pakuan"^^ . . . "Fakultas Matematika dan Ilmu Pnegetahuan Alam"^^ . . . "Program Studi Ilmu Komputer"^^ . . . . . . . "Student Final Project Topic Classification System Using the\r\nXGBoost Algorithm (Text)"^^ . . . "Laporan Skripsi Lengkap-Nabila Rasman Sutandi.pdf"^^ . . "HTML Summary of #8882 \n\nStudent Final Project Topic Classification System Using the \nXGBoost Algorithm\n\n" . "text/html" . . . "Ilmu Komputer"@en . .