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All Journal Jurnal Nasional Teknologi Informasi dan Aplikasinya
Wulandari, Desak Putu Sri
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Computer Science & IT

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Klasifikasi Tingkat Produktivitas Pegawai Garmen Menggunakan Algoritma Naive Bayes Wulandari, Desak Putu Sri; Suhartana, I Ketut Gede
Jurnal Nasional Teknologi Informasi dan Aplikasnya Vol 1 No 1 (2022): JNATIA Vol. 1, No. 1, November 2022
Publisher : Informatics Study Program, Faculty of Mathematics and Natural Sciences, Udayana University

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Abstract

Productivity level of garment employee classification aims to facilitate for companies to give appreciation to employees. In doing classification can use the Naïve Bayes Algorithm, which uses probability and statistical methods to predict opportunities base on experience. The classification of garment employees is categorized into three, namely low, medium, and high. The results of the classification of 1197 data employees, obtained 981 employees have high productivity, 190 employees with moderate productivity, 26 employees with low productivity. Evaluation on the classification obtained an accuracy value of 82.07% with a Root Mean Square Error (RMSE) value of 0,015731 which indicates that the classification carried out has a good classification model.
Co-Authors I Ketut Gede Suhartana