COMPARATIVE ANALYSIS OF PHISHING WEBSITE PREDICTION CLASSIFICATION ALGORITHM USING LOGISTIC REGRESSION, DECISION TREE, AND RANDOM FOREST
Abstract
Almost all daily activities are poured into the Internet, and users interact by
having a personal account that is linked to the world's data, by giving each
user access to view various information around the world through the
website. However, with the increasing number of users accessing the internet,
the confidentiality of internet users' data is increasingly vulnerable to being
stolen by irresponsible individuals or groups. Phishing is an attack in which
an attacker tries to steal confidential information from a target person by
sending a fake link. Attackers steal personal information entered by users on
fake websites. In comparing the prediction classification of phishing websites
using the logistic regression algorithm, decision tree
Downloads
References
Panjaitan, D. L., & Hasugian, P. M. (2021). Implementation of K-Nearest Neighbor Algorithm for Classification of Class Placement At Junior High School , Padang Month Issn : 2302-9706. Jurnal Infokum, 10(1), 43–49.
Sianipar, R., & Hasugian, P. M. (2020). Analysis of Service Levels in Café Black and White using Fuzzy Service Quality. Login: Jurnal Teknologi Komputer, 14(2), 128–136. http://www.login.seaninstitute.org/index.php/Login/article/view/41%0Ahttps://www.login.seaninstitute.org/index.php/Login/article/download/41/54
Siregar, V., & Hasugian, P. M. (2020). Application of Data Mining Method Using Association Rules Apriori To Shopping Cart Analysis On Sale Transactions (Case Study Alfamidi Burnt Stone). Journal Of Computer Networks, Architecture and High Performance Computing, 2(2). https://doi.org/10.47709/cnapc.v2i2.425
