Perancangan Sistem Klasifikasi Penerimaan Masyarakat Mengenai Mobil Sesuai Kebutuhan Dengan K-Nearest Neighbor (K-Nn)-Certainty Factor
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Institusion
Politeknik Negeri Jember
Author
Firmansyah, Willian Refky
Subject
458 - Teknik Informatika
Datestamp
2021-08-28 00:19:54
Abstract :
Based on the results of interviews and observations made at the Nissan Probolinggo dealership, 6 parameters were obtained to be used as variables in the study. The methodologies used in the research include requirements analysis, system design, implementation, and testing. The algorithm used is K-Nearest Neighbor and Certainty Factor. In the K-Nearest Neighbor method, it runs based on the training data tested and the number of data from the nearest neighbors or the number of K. While Certainty factor is a method that runs based on the assessment of experts in their fields, in this case, is a car expert. This system generates a classification for the new data and the confidence value of the inputted data. The accuracy of the KNN method used for classification is 80%.
Based on the results of interviews and observations made at the Nissan Probolinggo dealership, 6 parameters were obtained to be used as variables in the study. The methodologies used in the research include requirements analysis, system design, implementation, and testing. The algorithm used is K-Nearest Neighbor and Certainty Factor. In the K-Nearest Neighbor method, it runs based on the training data tested and the number of data from the nearest neighbors or the number of K. While Certainty factor is a method that runs based on the assessment of experts in their fields, in this case, is a car expert. This system generates a classification for the new data and the confidence value of the inputted data. The accuracy of the KNN method used for classification is 80%.
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