NURRAHMAN, FANDY (2021) IMPLEMENTATION OF NAÏVE BAYES ALGORITHM IN PREDICTING THE LENGTH OF TIME FOR UNIVERSTIAS MERCU BUANA ALUMNI TO GET A JOB AFTER GRADUATED. S1 thesis, Universitas Mercu Buana Jakarta.
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Abstract
Improving the quality of the university to have great accreditation, there are several things that need to be considered, one of them is utilizing alumni data. Alumni data obtained 2 years after they graduate can be used optimally to predict how long students get a job after they graduate. Attributes of the data that are being used are gender, judicial year. GPA, as well as the label of short, mid, or fast alumni getting a job, these attributes could be processed for prediction using classification. This research shows the results of using the Naïve Bayes Classifier (NBC) algorithm to train and test data in classifying the length of time taken by students based on data taken from the UMBCTC program, Tracer Study 2015, 2016, and 2017. From the results of the NBC method, data obtained will be validated using the K-Fold Cross Validation. The accuracy generated by NBC is 90% and the average K-Fold Cross Validation is 82.81% Keywords: Data Mining, Naїve Bayes Classifier, K-Fold, Cross Validation
| Item Type: | Thesis (S1) |
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| NIM/NIDN Creators: | 41517010021 |
| Uncontrolled Keywords: | Data Mining, Naїve Bayes Classifier, K-Fold, Cross Validation |
| Subjects: | 500 Natural Science and Mathematics/Ilmu-ilmu Alam dan Matematika > 510 Mathematics/Matematika > 518 Numerical Analysis/Analisis Numerik, Analisa Numerik 500 Natural Science and Mathematics/Ilmu-ilmu Alam dan Matematika > 510 Mathematics/Matematika > 518 Numerical Analysis/Analisis Numerik, Analisa Numerik > 518.1 Algorithms/Algoritma |
| Divisions: | Fakultas Ilmu Komputer > Informatika |
| Depositing User: | Dede Muksin Lubis |
| Date Deposited: | 10 Jul 2024 01:44 |
| Last Modified: | 10 Jul 2024 01:44 |
| URI: | http://repository.mercubuana.ac.id/id/eprint/67074 |
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