Metode Naive Bayes Dalam Menentukan Program Studi Bagi Calon Mahasiswa Baru

  • Wildani Eko Nugroho Politeknik Harapan Bersama Tegal
  • Ali Sofyan Politeknik Harapan Bersama
  • Oman Somantri Politeknik Negeri Cilacap
Abstract views: 80 , PDF downloads: 362


In a university, determining a study program for prospective students is something that is often done to focus on prospective students so that they are in accordance with their competencies. This is a very important hope, because prospective students can develop self-competence according to their academic abilities. This research method uses several stages, including data cleaning, data collection, determining criteria, determining probability, and final testing. The Naïve Bayes method with a case study at the Private Madrasah Aliyah PAB 6 Helvetia and testing of 100 student data with an accuracy rate of 90% is a previous research. The purpose of this study was to make a classification of majors based on the criteria, while in this study the aim of making a classification of study programs for prospective new students. In this study, the same method was used but the number of data records was different, the test data was 1671 student data records, the data was obtained from 2256 data records.From the total data records were 2256, after data cleaning and data collection were carried out, 1671 test data were obtained. In the test data, there are several probability values that contain various criteria and attributes used to determine the classification of study programs for prospective new students. The number of data records is divided into 2 parts, the first is used for training data with 1158 data with a percentage of 70%, and testing data with 513 data records with a percentage of 30%. From the test results with the same method with different number of data records, the accuracy rate is from 90% to 96% with an accuracy value of 96.68%. From this accuracy value shows that the classification results obtained show the Pharmacy DIII study program.

PlumX Metrics