Penerapan Data Mining Untuk Memprediksi Daya Serap Lulusan Siswa Menggunakan Algoritma Native Bayes - Waru, Daka; Astuti, Reny Wahyuning; Kahar, Novhirtamely (Institut Agama Islam Negeri (IAIN) Curup, 2021)
The importance of predicting the absorption of Vocational High School (SMK) graduates in the world of work, especially SMK Negeri 9 Muaro Jambi which is not yet known about the prediction of the world of work that accepts SMK graduates so that the purpose of this study is to analyze the prediction of the accuracy of the absorption of graduates of SMK Negeri 9 Muaro Jambi as material. a reference to see whether the graduates of SMK Negeri 9 Muaro Jambi have achieved the expected goals or not so that this analysis can be used as input for schools to improve the competence of SMK students. This implementation is assisted by using the Rapidminer and WEKA applications with 100 alumni work data input. The attributes used in this analysis process are Department, Waiting Time and Field of Work and Class of Work Field Accuracy. The process in this analysis is carried out with data that has been provided with the NaÃ¯ve Bayes Classification Method to predict the absorption of graduates. The results of this study the highest accuracy value in the Rapidminer application is at 100% and WEKA is at 100%.