KLASIFIKASI KUALITAS TEMBAKAU LAYAK PANEN DENGAN NAIVE BAYES CLASSIFIER DI DUSUN KAMPONG SITUBONDO - Muhammad Yasin; Zaohol Fatah (Jurnal Ilmiah Multidisiplin Ilmu, 2024)
To classify the quality of tobacco that is suitable for harvest in Dusun Kampong using the Naive Bayes Classifier algorithm. Tobacco as a plantation commodity has high economic value, both in the domestic and international markets. This study uses a qualitative method with data collection through direct observation and interviews with local tobacco farmers and traders. The Naive Bayes algorithm is applied to predict harvest eligibility based on the attributes of height, leaf width, leaf length, and number of leaves. Testing is done manually and using the RapidMiner tool to produce accurate predictions. The results of the study show the effectiveness of the Naive Bayes algorithm in classifying tobacco quality.