Jurnal Teknik Komputer AMIK BSI
Vol 3, No 2 (2017): JURNAL TEKNIK KOMPUTER AMIK BSI

PENERAPAN ALGORITMA NAÏVE BAYES UNTUK KLASIFIKASI BAKTERI GRAM-NEGATIF

Evy Priyanti (AMIK BSI Jakarta)



Article Info

Publish Date
01 Aug 2017

Abstract

The classification depends on the variety of bacteria that exist. The important feature to identify an organism of bacterial phenotype is the scheme that utilizes the morphology and staining properties of the bacteria itself, to classify the phenotype scheme is used Naïve Bayes algorithm that has proven to have a high degree of accuracy and high rate of speed when applied into E.coli dataset in E. coli dataset consisting of seven features are: mcg, gvh, lips, chg, aac, alm1, alm2, and proteins are classified into 8 classes: cytoplasmic (cp), an inner membrane without the signal sequence (im), perisplasm (pp), in the membrane with uncleavable signal sequence (IMU), outer membrane (oM), outer membrane lipoprotein (OML), the membrane lipoprotein (IML), an inner membrane with cleavable signal sequence (IMS) with an accuracy of 80.93%, with Naïve Bayes algorithm so it can be ascertained that the classification of gram-negative bacteria with E. coli phenotype datasets prove to be accurate.

Copyrights © 2017






Journal Info

Abbrev

jtk

Publisher

Subject

Computer Science & IT

Description

Jurnal Teknik Komputer merupakan jurnal ilmiah yang diterbitkan oleh LPPM Universitas Bina Sarana Informatika. Jurnal ini berisi tentang karya ilmiah hasil penelitian yang bertemakan: Networking, Robotika, Aplikasi Sains, Animasi Interaktif, Pengolahan Citra, Sistem Pakar, Sistem Komputer, Soft ...