KLASIFIKASI TEBU DENGAN MENGGUNAKAN ALGORITMA NAìVE BAYES CLASSIFICATION PADA DINAS KEHUTANAN DAN PERKEBUNAN PATI

The various kind of sugarcane causes the difficulty in classification and selection of productive cane in Pati, so that the level of success of the industry and farmers in the cultivation of sugar cane is less effective. The impact is the production of sugar cane becomes less appropriate to the level of the national sugar requirement. Plantation sector is the mainstay in Pati and the most significant plantation commodities are sugar cane. The production of sugar cane in Pati is the largest one in Central Java. To support self-sufficiency program in Indonesia, the initial stage is to increase the production and productivity of sugarcane. To overcome the problem of improvement of classification accuracy in determining the type of cane required a calculation that applies a method that can classify productive sugarcane varieties in accordance with the attributes of the data of Forestry and Plantation Department in Pati. By using the calculation of Naïve Bayes classifier method which is a probabilistic classification technique based on Bayes theorem using the assumption of the absence of linkages between the attributes in the classification process. This study aims to apply the methods of Naïve Bayes classification in sugarcane classification based on sugarcane productive and non-productive class with certain criteria can be said to be productive or not using validity Confusion matrix C, which can be said to be productive or not in the performance percentage of 73.3% which is caused by the number of continuous data compared with discrete data