Open AccessLine Bot Chat Filtering using Naïve Bayes Algorithm
Author(s) -
Nathania Elvina*,
Andre Rusli,
Seng Hansun
Publication year - 2019
Publication title -
international journal of innovative technology and exploring engineering
Language(s) - English
Resource type - Journals
ISSN - 2278-3075
DOI - 10.35940/ijitee.l3726.1081219
Subject(s) - naive bayes classifier , computer science , instant messaging , bayes' theorem , algorithm , class (philosophy) , machine learning , artificial intelligence , process (computing) , simple (philosophy) , precision and recall , recall , line (geometry) , world wide web , mathematics , bayesian probability , support vector machine , psychology , philosophy , geometry , epistemology , cognitive psychology , operating system
Instant messaging has changed and simplified the way people communicate, whether in professional or personal life. Most communication is done through instant messaging, and it is common for people to miss important information. This is due to the huge amount of incoming message notifications, so users tend to accidentally ignore them. This is also experienced by Universitas Multimedia Nusantara (UMN) student committees who communicate via LINE instant messenger. This research showed LINE bot was made by using the Naive Bayes algorithm to classify between important messages and unimportant messages on the committee group. The Naive Bayes algorithm is a classification algorithm based on probability and statistical methods. The Naive Bayes algorithm is chosen because it is widely implemented in spam filtering; the method is simple and has good accuracy. The classification process is done by calculating the probability of chat in each class based on the value of the word likelihood which generated in the training process. This research produces spam precision and spam recall as 94.2% and 95.6% respectively