Pemodelan Terhadap Kelulusan Siswa Masuk Kelas Akselerasi Menggunakan Analisis Regresi Logistik Dan Multivariate Adaptive Regression Spline (MARS)
Abstract
Regression Analysis is a statistical methodology that usually used for analyzing the relationship between a response and one or more predictor. When the response is categorical variable, then the regression methods that could be used are Logistic Regression and Multivariate Adaptive Regression Spline (MARS). The result of both modeling can be used to classify the objects. The aim of this research is to find a quantitative model for explaining factors that influenced the success of students in joining the acceleration class. Evaluation the accuracy of classification rate is done by implementing Press Q statistic test. The result of Logistic Regression shows that the classification accuracy is 74,8 where as MARS yields 77,7. Hence, MARS model is the best model for evaluating the success factor of student in joining the acceleration class.
Downloads
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License
An author who publishes in the ARIKA Jurnal agrees to the following terms:
- The author retains the copyright and grants ARIKA journal the right of first publication of the work simultaneously licensed under the Creative Commons Attribution-ShareAlike 4.0 License that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this journal.
- The author is able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book) with the acknowledgment of its initial publication in this journal.
- The author is permitted and encouraged to post his/her work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of the published work (See The Effect of Open Access).
