Implementasi Algoritma Naïve Bayes untuk Klasifikasi Pemahaman Program MBKM bagi Mahasiswa
DOI:
https://doi.org/10.31599/40dppk38Keywords:
Classification, Data mining, MBKM Program, Students, SurveyAbstract
Outcome based education is the basis for the Informatics Study Program at Bhayangkara Jakarta Raya University (Ubhara Jaya) in formulating graduate profiles. Research to identify student knowledge related to MBKM. The analytical approach ranks 25 questions in the MBKM program which are the focus of students and lecturers. Through the survey conducted, it will provide an overview of whether the MBKM program has an attraction for students to develop their competencies, skills and soft skills as a provision for future graduates. In addition, do students and lecturers assess the MBKM program as having significant benefits in improving
student abilities? The research was conducted by implementing data mining survey results of students and lecturers in depth. The method used is a classification learning ensemble. The classification process begins with collecting available data, preprocessing data in the form of feature selection, cleaning, integration, and transformation; continued with the process of making models on training data by applying 10-fold cross validation and the assembly learning method to handle imbalance classes; and finally evaluation of modeling results on data testing. The output target of this research is a policy recommendation for implementing the MBKM
program for the Ubhara Jaya Informatics study program.
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