KLASIFIKASI BUAH NANAS MENGGUNAKAN METODE NAÏVE BAYES

Pineapple is one of the tropical fruit commodities produced in Indonesia, one of the pineapple producing areas is Subang Regency, West Java. Currently, pineapples are produced to meet various needs, namely traditional markets, supermarkets, pineapple processing factories, and even souvenirs from Subang Regency. This study aims to classify pineapples that are suitable for sale using the Naïve Bayes method, which is known to be simple and effective in processing probabilistic data. This study uses primary data that includes the physical characteristics of pineapples such as skin color and sweetness level (Brix). The data is processed through several stages, including preprocessing and classification with Naïve Bayes. The results of the study showed a classification accuracy level of 94%, with satisfactory performance on recall and precision. The limitation of this method is the assumption of independence between features, which affects accuracy in certain cases. This study makes a significant contribution to the application of artificial intelligence in the agricultural sector and opens up opportunities for development in other fruit commodities.