Penerapan Algoritma Naive Bayes Classifier Untuk Klasifikasi Judul Skripsi Berdasarkan Konsentrasi - Dania, Salmin Dania; Rezqiwati Ishak; Hastuti Dalai (Teknik Informatika Fakultas Ilmu Komputer Universitas Ichsan Gorontalo, 2024)
Abstract The application of the Naive Bayes Classifier algorithm to classify thesis titles based on concentration is research that aims to develop a classification system for thesis titles based on concentration using the Naive Bayes Classifier algorithm. This classification system helps students determine the thesis concentration that suits their interests and abilities. This research uses thesis title data from the Informatics Engineering Department, Faculty of Computer Science, Universitas Ichsan Gorontal. It employs data attributes in the form of thesis title and concentration. The data are cleaned and preprocessed before being used for algorithm training and testing. The implementation of the Naive Bayes Classifier algorithm is through the Python programming language. The research results show that the Naive Bayes Classifier algorithm can classify thesis titles with an accuracy of 80% in the model evaluation process using the Confusion Matrix. The results indicate that the Naive Bayes Classifier algorithm is an effective alternative for classifying thesis titles based on concentration. Keywords: classification, thesis title, concentration, Python, Confusion Matrix, Naive Bayes Classifier