Comparison of Social Media BOT Functions Using the K-Nearest Neighbor Method Against User Satisfaction

Nayny Frastika; Yunita Yunita

doi:10.31294/inf.v11i2.22056

Comparison of Social Media BOT Functions Using the K-Nearest Neighbor Method Against User Satisfaction

Nayny Frastika, Yunita Yunita

Abstract

Social media is currently an alternative medium in conveying messages in the form of news and can be used as a tool to exchange news from different places. Many people use social media to express opinions, express feelings, as well as experiences and things that can be of concern. In this study, the data processing used was the K-Nearest Neighbor Algorithm with the classification method as a media for comparing the functions of the two bots, namely the WhatsApp and Telegram bots. Using SPSS (Statistical Product and Serive Solutions) and Rapidminer as a place to perform calculations and analysis. Based on the results of testing data mining with Rapid Miner, the calculation results are obtained which will be used as information to support user satisfaction in using Social Media Bots. User satisfaction is found in WhatsApp Bot users 72.22% and Telegram Bot users 28.57%. Calculations are carried out with a data mining process obtained from the K-Nearest Neighbor algorithm to make it easier to find Bot user satisfaction on both WhatsApp and Telegram social media. The WhatsApp bot is the best choice and has several useful functions as a digital communication media tool on the Internet of Things.

Keywords

Bot Functions, K-Nearest Neighbor (KNN), User Satisfaction

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References

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DOI: https://doi.org/10.31294/inf.v11i2.22056