Implementation of a Decision Support System for Employee Reward and Contract Extension Using Naïve Bayes - Ningsih, Nur Ristia; Fitriasih, Fitriasih (Program Studi Informatika, 2026)
This study implements an integrated Decision Support System (DSS) for evaluating employee potential for both reward allocation and contract extension at PT Java Abadi Gemilang. Unlike previous studies that focus on a single human resource decision, this system combines two critical functions into one framework. Using the Naïve Bayes classifier within the CRISP-DM methodology, the system was tested on 350 employee records from January 2022 to December 2023. Eight key attributes were selected using Information Gain. Experimental results show that the model achieves 92.50% accuracy, 91.80% precision, 93.20% recall, and 92.45% F1-score. The DSS implementation improved evaluation objectivity based on preliminary survey feedback and reduced processing time from two weeks to real-time, representing a 75% increase in administrative efficiency. The main contribution is the integration of reward and contract extension decisions into a single rule‑based system that adapts to divisional characteristics.