Pemetaan Sebaran Asal Siswa dan Klasifikasi Jarak Asal Siswa SMA Negeri di Kabupaten Pringsewu Menggunakan Metode Naive Bayes - Riska Aprilia; Kurnia Muludi; Aristoteles Aristoteles (Jurnal Komputasi, 2016)
Distance students can be seen from the data stored student's address. Address high school students in the Pringsewu District have different distances. This research was conducted to determine the classification of the distance stored in high school students in the Pringsewu District. Distance students are classified to obtain five categories: "sangat dekat", "dekat", "sedang", "cukup jauh",  and "jauh" by using eight attributes are "nomor", "SMA", "kabupaten", "kecamatan", "kelurahan", "jarak", "asal SMP", and "class". The classification performed by using Naive Bayes using Weka tool. Distribution of training data and testing data is defferent as much as 20 times of testing, resulting in the highest accuracy Naive Bayes is 89.329% on distribution of 60% training data : 40% testing data. The data of students address and information classification results displayed in the form of digital map that is mapping of student's address in high school in the Pringsewu District.