Naïve Bayes for Analysis of Student Learning Achievement

Student achievement is measured by the index value obtained every semester,student several factors, and in this research author takes factors including study paths, choice of majors, monthly living expenses, relationships with friends, family, motivation study, employment, scholarships, transportation, internet services. Analysis prediction student using Naïve Bayes Algorithm classification method, result algorithm works very well 14 datasets to determine grades 15th student. Based on theAnalysis, variables that affect include residence, job, scholarships. The accuracy naïve bayes for case model reaches 60%, precision 25%, recall 100%.