SISTEM PENDUKUNG KEPUTUSAN SELEKSI PENERIMA BEASISWA DENGAN METODE NAÏVE BAYES

  • Qori Alfina Pratiwi Universitas Stikubank
  • Jati Sasongko Wibowo Unisbank Semarang
Keywords: Scholarships, Recipients, Naïve Bayes Classifier, Data Mining

Abstract

Lot of problems arise in selecting scholarship recipients in a large number of submissions, the existence of several searches used, and the selection of files for scholarship applicants is still manual, so a system is needed that can speed up, help, and make it easier in the decision-making process to lighten work. student section. In supporting decisions this system will use the Naïve Bayes Classifier Method to determine what is acceptable and not acceptable. The NBC method can analyze and make improvements to old data, and the resulting data will provide simpler probability values that can later be used to make decisions. From the results of the research that has been carried out, it can be realized that the application of the data mining algorithm using the Naïve Bayes Classifier can be carried out to select scholarship recipients at Stikubank University Semarang. The result of the selection of Unisbank Semarang scholarship recipients is the accuracy value. 72% of the 135 data which is divided into 100 training data and 35 test data.
Published
2023-07-14
How to Cite
[1]
Qori Alfina Pratiwi and Jati Sasongko Wibowo, “SISTEM PENDUKUNG KEPUTUSAN SELEKSI PENERIMA BEASISWA DENGAN METODE NAÏVE BAYES ”, ELKOM, vol. 16, no. 1, pp. 156-162, Jul. 2023.