PENERAPAN ALGORITMA NAÏVE BAYES UNTUK KLASIFIKASI BAKTERI GRAM-NEGATIF
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.
Penulis: Evy Priyanti
Kode Jurnal: jptkomputerdd170139
