Implementasi Algoritma Naïve Bayes Untuk Prediksi Persentase Kelulusan Ujian SIM (Studi Kasus Satpas Daan Mogot)
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Institusion
Institut Teknologi Perusahaan Listrik Negara
Author
Nugroho, Satrio Dwi
Sudirman, M. Yoga Distra
Luqman, Luqman
Sudirman, M. Yoga Distra
Luqman, Luqman
Subject
Teknik Informatika
Datestamp
2022-09-27 03:56:54
Abstract :
The diversity of the SIM group in Satpas Daan Mogot has a percentage of different SIM graduation exams and there are still many people who do not pass driver license exams due to lack of knowledge about traffic signs or still less proficient in driving motor vehicles. In this study, the design used is using Data Flow Diagrams (DFD). The method used in this research is naïve bayes algorithm. The purpose of this study is to develop applications for predict the percentage of pass driver lisence exams using the web-based naïve bayes algorithm at Satpas Daan Mogot for predict of someone?s pass driver lisence exams, find out whether naïve bayes can be used to predict pass driver lisence and to know the accuracy of the naïve bayes algorithm to pass driver license data. The criteria used to predict pass of driver license exam are group of age, educational stage, gender, health, group of driver lisence. Testing the system using Black Box and testing the accuracy of the method using confusion matrix. The accuracy of the naïve bayes algorithm is 95%.
The diversity of the SIM group in Satpas Daan Mogot has a percentage of different SIM graduation exams and there are still many people who do not pass driver license exams due to lack of knowledge about traffic signs or still less proficient in driving motor vehicles. In this study, the design used is using Data Flow Diagrams (DFD). The method used in this research is naïve bayes algorithm. The purpose of this study is to develop applications for predict the percentage of pass driver lisence exams using the web-based naïve bayes algorithm at Satpas Daan Mogot for predict of someone?s pass driver lisence exams, find out whether naïve bayes can be used to predict pass driver lisence and to know the accuracy of the naïve bayes algorithm to pass driver license data. The criteria used to predict pass of driver license exam are group of age, educational stage, gender, health, group of driver lisence. Testing the system using Black Box and testing the accuracy of the method using confusion matrix. The accuracy of the naïve bayes algorithm is 95%.
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