Abstract
Classification method is a statistical method for grouping or classifying data. A good classification method will produce a little bit of misclassification. Classification method has been greatly expanded and two of the existing classification methods are Multivariate Adaptive Regression Spline (MARS) and Fuzzy k-Nearest Neighbor in Every Class (FK-NNC). This study is aimed to compare a classification of Keluarga Berencana participation based on suspected factors that affect them between the methods of MARS and FK-NNC. This study uses secondary data which one is the participation of Keluarga Berencana in Semarang on 2014. Evaluation of errors use an Apparent Error Rate (APER). In the method MARS best classification results is obtained with the combination of BF = 24, MI = 3, MO = 0 for generating a smallest Generalized Cross Validation (GCV) value and the APER is obtained by 19%. While FK-NNC method is obtained the best classification results in k = 3 for generating the greatest accuracy of classification value and APER value is obtained by 22%. Based on APER (Apparent Error Rate) calculation, it shown that the classification of family participation in Keluarga Berencana (KB) programs in Semarang using MARS method is better than FK-NNC method. Keywords: Classification, MARS, FK-NNC, APER, Keluarga Berencana
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.