IAES International Journal of Artificial Intelligence (IJ-AI)
Vol 10, No 2: June 2021

Measure the effectiveness of information systems with the naïve bayes classifier method

Agung Triayudi (Universitas Nasional)
Sumiati Sumiati (Universitas Serang Raya)
Saleh Dwiyatno (Universitas Serang Raya, Indonesia)
Dentik Karyaningsih (Universitas Serang Raya)
Susilawati Susilawati (Universitas Mathla'
ul Anwar)



Article Info

Publish Date
01 Jun 2021

Abstract

Technological advances at this time are developing very fast, information systems became the frontline in technological advancements, the need for information systems to support jobs is increasingly high. However, its implementation for users does not have a significant impact, so that it needs to be reviewed and re-evaluated in the use of the information system built. The naive bayes classifier method can provide "effective" and "ineffective" conclusions and is used as material for evaluation and improvement. The purpose of this study is to contribute to measuring the effectiveness of the information system, to solve problems with the naïve bayes classifier method approach which has advantages in the process of classifying data and predicting data. From the test results three times, training has been conducted using 100 data, accuracy value of 84.82% and error 15.18%.

Copyrights © 2021






Journal Info

Abbrev

IJAI

Publisher

Subject

Computer Science & IT Engineering

Description

IAES International Journal of Artificial Intelligence (IJ-AI) publishes articles in the field of artificial intelligence (AI). The scope covers all artificial intelligence area and its application in the following topics: neural networks; fuzzy logic; simulated biological evolution algorithms (like ...