Open AccessPublication of the society’s sensitive personal data in the legitimate site of the general election committee
Author(s) -
A.A. Gede Oka Parwata,
Kadek Yota Ernanda Aryanto,
Dewa Gede Hendra Divayana
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1516/1/012005
Subject(s) - marital status , personally identifiable information , government (linguistics) , hyperlink , general election , internet privacy , computer science , political science , medicine , world wide web , law , web page , environmental health , population , linguistics , philosophy , politics
It is highly important to protect the society’s sensitive personal data. The reason is that many personal data are published by the government institution without paying attention to the prevailing regulations. In this current study, the search for the data in the form of hyperlink with its contents in the legitimate site of the General Election Committees was conducted with the assistance of Crawling Web. The obtained contents were preprocessed using the Preprocessing Text, which were then weighted using the TF-IDF method before they were classified using the Naїve Bayes method. After that, an analysis on the types of the published sensitive personal and the extent of the publication based on the area groups was conducted. Out of 6,700 instances of the personal data which were analyzed, 6.430 were published. The personal data which were published were full name, place and date of birth, religion, marital status, ID Number of the government civil servants, identity card number, number of the tax payer, account number, mobile number, e-mail, address, position, and face photo. The level of publication based on the total data found was as follows: 11.45% in the Central General Election Committee, 21.60% in the eastern area, 17.01% in the central area and 49.94% in the eastern area. The accuracy of the Naїve Bayes method averaged 96.99%. Prior to publication, the General Election Committee is recommended to respect someone’s personal data as privacy and the data which would be published should obtain approval and an easily-contacted contact person.