Line Bot Chat Filtering using Naïve Bayes Algorithm
Nathania Elvina1, Andre Rusli2, Seng Hansun3
1Nathania Elvina, Informatics Department, Universitas Multimedia Nusantara, Tangerang, Indonesia.
2Andre Rusli, Informatics Department, Universitas Multimedia Nusantara, Tangerang, Indonesia.
3Seng Hansun, Informatics Department, Universitas Multimedia Nusantara, Tangerang, Indonesia.
Manuscript received on September 14, 2019. | Revised Manuscript received on 24 September, 2019. | Manuscript published on October 10, 2019. | PP: 4877-4882 | Volume-8 Issue-12, October 2019. | Retrieval Number: L37261081219/2019©BEIESP | DOI: 10.35940/ijitee.L3726.1081219
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: 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.
Keywords: Bot, Chat Filtering, Committee Group, Naïve Bayes, Organizational Interest.
Scope of the Article: Algorithm Engineering