Article Per Year (5 Year)
p-Index From 2021 - 2026
0.23
P-Index
This Author published in this journals
All Journal International Journal Of Science, Technology & Management (IJSTM)
Roni Anagora, Roni Anagora
Unknown Affiliation
Aerospace Engineering Agriculture, Biological Sciences & Forestry Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Mechanical Engineering Transportation

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
The Classification of Phishing Websites using Naive Bayes Classifier Algorithm Roni Anagora, Roni Anagora; Rudini , Rudini; Rohmat Taufiq , Rohmat Taufiq; Ahmad Dedi Jubaedi , Ahmad Dedi Jubaedi; Rio Wirawan, Rio Wirawan; Arman Syah Putra
International Journal of Science, Technology & Management Vol. 3 No. 2 (2022): March 2022
Publisher : Publisher Cv. Inara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46729/ijstm.v3i2.498

Abstract

The background of this research is how to find out the selected websites which are classified through the naive Bayes classifier algorithm. With this algorithm, it can be seen how far the classification of Phishing is. The method used in this study is to use experimental methods or research on the data obtained, these tests will include new data that can be accounted for and can determine whether the data is suitable for use. The problem raised in this study is how to find out which principles have been clarified with the dizziness method using the naive Bayes classifier algorithm, with the algorithm, which websites can be classified properly. The purpose of this study is how to find out the data tested through training data will produce new data, especially well for items and produce from values Naive Bayes algorithm obtained an average accuracy value of 92.98% with a TP Rate of 0.930%, FP Rate of 0.076%, Precision of 0.930%, Recall of 0.930% and Fmeasure of 0.930%.
Co-Authors Ahmad Dedi Jubaedi , Ahmad Dedi Jubaedi Arman Syah Putra Rio Wirawan, Rio Wirawan Rohmat Taufiq , Rohmat Taufiq Rudini , Rudini