Pembuatan Aplikasi Data Mining Untuk Memperediksi Masa Studi Mahasiswa Menggunakan Algoritma Naive Bayes - Victor Tarigan (Jurnal Informatika, 2023)
Data mining is a series of processes to obtain additional value information that is not known manually from a database. Data mining also manages experience or even mistakes in the past to improve the quality of the analysis model, one of which is the learning ability of data mining techniques, namely classification. Class is a learning task that is a new object into one of the class labels or categories on the old object that has been previously defined. This classification uses one method of data mining algorithm that is Naive Bayes.Naive Bayes algorithm works based on a certain distance between two objects by setting the value of k. The value of k is a parameter to determine the distance between the new object to the old object.By using the data mining technique, the university can obtain student academic data, namely the Achievement Index (IP) to predict the student's study period.In this data mining application consists of data testing and data training with NIM input.PHP and the database used is MySQL.The results of this data mining application this system can predict the results of the classification of student study period based on GPA 4 first semester, the average value of high school time, and grades in high school.