Sistem Pendukung Keputusan Kenaikan Jabatan Menggunakan Metode Algoritma Naïve Bayes Classifier - Dewi, P S; Sastradipraja, C K; Gustian, D (Jurnal Teknologi dan Informasi (JATI), 2021)
This research aims to build an information system that can support the company in decision-making, especially about the promotion of positions at PT. Global Beautiful Fashion. This is motivated by the difficulty of determining whether or not an employee has been promoted to office, due to an uncomputed system and stacked employee data documents. In this study, the data used is data on the promotion of employee positions at PT. Global Beautiful Clothing and the method used is the Naïve Bayes Classifier algorithm method. And to find out how well the Naïve Bayes Classifier algorithm was used in this study, RapidMiner software was used to conduct testing. RapidMiner's testing yielded an accuracy score of 91.67% and a ROC value of 0.979 which means the Naïve Bayes Classifier algorithm was very well used in this study. After testing using RapidMiner software and obtaining test results, it is then implemented into a system using PHP and MySQL designed to predict promotion. The prediction results obtained from the system are following the calculation results obtained from RapidMiner software and manual calculations. Based on the research that has been done that the decision support system built can be applied to PT. Busana Indah Global (BIG) to make it easier to determine the feasibility of promotion for its employees.