KLASIFIKASI MUTU BERAS MENGGUNAKAN K-NN BERBASIS BACKWARD ELIMINATION

CLASSIFICATION RICE QUALITY USING K-NN BACKWARD-BASED ELIMINATIONRice is one of the most important agricultural products. And it a strategic commodity because almost all Indonesian people need it. Because importance function rice as staple food ingredient, quality to be consumed must ensured high quality. Determination or until now has been done by many previous researchers. However, several methods that have selected, majority use image processing. Rice data processing using mining still rarely done. In this study, dataset will used comes from Probolinggo Regency Agriculture Service database which 1 special attribute and 9 regular attributes. The attributes are: variety, length, shape, color, taste, planting technique, season, pests, PH method in study backward elimination-based method.From results analysis computation methods, can concluded increase accuracy classification resulted conclusions. Namely affect determination are pests PH. While features considered no effect taste length. As for much 4952, best 83.08% when k = 1, while 2000, then 87.70% at 1000, 98.60%, namely k=1.