Pembagian Task Karyawan Berdasarkan Riwayat Kerja dengan Metode Naive Bayes

Nashihah, Mustafidatun and Aminah, Siti and Maulidi, Rakhmad (2022) Pembagian Task Karyawan Berdasarkan Riwayat Kerja dengan Metode Naive Bayes. Journal of Applied Informatics and Computing (JAIC), 6 (2). pp. 187-193. ISSN 2548-6861

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Official URL: https://jurnal.polibatam.ac.id/index.php/JAIC/

Abstract

Accuracy and suitability in the division of employee tasks have an important role in the division of employee tasks, in order to obtain a list of criteria that are in accordance with the abilities of employees in one division. PT. Assist Software Indonesia Pratama is currently still in manual division of tasks, namely by sorting out tasks based on features, applications, divisions, and employees who usually do the work. So that it takes a long time in the process of dividing employee tasks, one of the factors is HRD must sort out tasks based on features, applications in order to determine the division and employees who work on the task. The purpose of the research is to facilitate the division of tasks to employees in order to get a list of criteria that are in accordance with the abilities of employees in one division using the Naive Bayes method. So we need a system that can help HRD in distributing employee tasks in accordance with the division and employee capabilities. In this task distribution system using the Multinomial Naïve Bayes Classifier method as a determinant of employee task distribution. The division of employee tasks is based on the tasks that have been done by the previous employee, so that the system can perform the appropriate task division. The system can see the similarities between tasks using the Multinomial Naïve Bayes method as a consideration for determining the divisions and employees who work with the percentage accuracy of 92.5% and 82.5%.

Item Type:	Article
Subjects:	Theory of computation > Theory and algorithms for application domains
Divisions:	Engineering Sciences
Depositing User:	Unnamed user with username editor_perpustakaan
Date Deposited:	08 May 2024 06:54
Last Modified:	08 May 2024 06:55
URI:	http://repository.stiki.ac.id/id/eprint/2096

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