Penerapan Algoritma Weighted Product untuk Penentuan Pegawai Terbaik Badan LITBANG

Abstract

The Ministry of Home Affairs at the Research and Development Agency (LITBANG) conducts the selection of the best employees to boost employee morale in increasing employee loyalty or loyalty to government agencies and to evaluate the performance of employees from each division. The selection of the best employees has been done periodically or periodically but has not been optimal in its implementation. The Ministry of Home Affairs at the Research and Development Agency found obstacles in determining the selection of the best Employees. Constraints faced are when finding the same final value when the assessment has been carried out and there is a subjective assessment that is assessing someone based on the closeness of the assessment staff so that the Head of Research and Development has difficulty when deciding who the best employee is, this often results in errors in determining the best employee at LITBANG Agency. The application of the Weighted Product (WP) Algorithm is used to determine the best employee at the Ministry of Interior Research and Development Agency. The final result of the system is a report on the best employees based on the Weighted Product algorithm to get the average distance between manual results with Weighted Products of 4.05 with a standard deviation of 3.017 and the classification process with Naïve Bayes produces an accuracy of 66.67% and an error of 33.33%, with the error value, the results of the classification still have shortcomings in predicting the eligibility of the best employees. Applications can assist decision makers in deciding who employees are entitled to become the best employees at the Research and Development Agency.