IMPLEMENTASI METODE KLASIFIKASI NAIVE BAYES DALAM MEMPREDIKSI PRODUKTIVITAS HASIL PERTANIAN BAWANG MERAH DIBREBES MENGGUNAKAN RAPIDMINER

Abstract

This study aims to predict the productivity of onion harvest using Naive Bayes method, considering that the agricultural sector is an important pillar of the nation's economy. This method is applied to calculate the success rate of crop productivity prediction in the midst of challenges in the form of changes and developments that increase the complexity of data and information. Research Data obtained through the website of the Central Bureau of Statistics of Brebes regency. The results showed that variables such as seed type, treatment, irrigation, disease, and fertilizer significantly affect onion productivity. Naive Bayes method proved effective in classifying data and producing accurate predictions, so it can be implemented to support decision making in agriculture