DATA MINING IDENTIFIKASI WEBSITE PHISING MENGGUNAKAN ALGORITMA C4.5

Tomy Salim, Yo Ceng Giap

Abstract


The background of this research is to help internet users around the world to be more careful and avoid phishing websites while surfing in cyberspace. The faster development of information technology and number of big websites is increasing every day, the more likely an internet user to accidentally open a phishing website. With that reason, research on phishing websites that are very harmful to internet users is seemed necessary. To solve this problem, the author uses a data mining model to search for patterns that contains information on a large number of sample website data. Data mining method used in this research is Decision Tree because the result is suitable and satisfying. In this study, the author used sample data from a website named uci dataset, which on that website page there are many data sets that can be used for researching and academic interests. From a large number of data rows, the author managed to find several factors that can be used as references or signs of phishing websites. Based on the evaluation result of data mining, this research has met the provisions of data mining research requirements by the university and this study also shows results as the author expected.


Keywords


Data Mining, Phishing, Website, Internet, Decision Tree, Research, Algorithm, C4.5

Full Text:

PDF

References


Han, Jiawei., Kamber, Micheline dan Pei, Jian. (2012). Data Mining Concepts and Techniques Third Edition. Elsevier Inc; Amsterdam.

Land, Sebastian dan Fischer, Simon. (2012). Rapid Miner 5. Rapid-I GmbH; Dortmund.

Mohammad, Rami M., Thabtah, Fadi dan McCluskey, Lee. (2014). Predicting Phishing Websites based on Self-Structuring Neural Network. University of Huddersfield; Huddersfield. ISSN 0941-0643.

Nikam, Sagar S. (2015). A Comparative Study of Classification Techniques in Data Mining Algorithms. Techno Research Publishers; Bhopal. ISSN 0974-6471.

Parthasarathy, G., Tomar, D. C. dan Praisy, K. Christina. (2016). An Enhancement Of Association Classification Algorithm For Identifying Phishing Websites. Indian Journal of Computer Science and Engineering; Chennai. ISSN : 0976-5166


Refbacks

  • There are currently no refbacks.


View My Stats

 

Creative Commons License
Jurnal TAM is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.