3rd Asia Pacific International Conference on Industrial Engineering and Operations Management


Adena Wahyu Gumelar, Tacbir Hendro Pudjiantoro & Puspita Nurul Sabrina
Publisher: IEOM Society International
0 Paper Citations
Track: Undergraduate Student Paper Competition


NFT, or non-fungible tokens, are online certificates of ownership that can be traded based on data units stored in digital ledgers belonging to blockchain technology. This is non-fungible, meaning that it cannot be exchanged and is unique. NFT has been around since 2014. But now, it is increasingly being considered a fairly practical method for trading digital artwork or art. To buy NFT assets, you require special coins in the form of NFT coins, which consist of various types, such as mana coins, sand, axs, and other NFT coins. The NFT coins are used to process NFT purchase transactions. The movement of NFT coins over time is relatively erratic and uncertain. This NFT coin price prediction will be very useful for investors to know how the investment flow of each price works because the price of each NFT coin will change from time to time. through the literature study stage, interviews, and viewing daily NFT coin price data where the attributes used are date, open, high, low, close, and volume. The method used in this research is k-Nearest Neighbors. Dataset collection through the website www.coinmarketcap.com for the period January 1, 2019 to December 31, 2021. Then the data processing is carried out. An accurate NFT coin price prediction model can help investors in considering transaction decisions because NFT coin prices, which tend to be non-linear, will allow investors to make predictions. This study aims to obtain the predicted value of NFT coins using the k-Nearest Neighbors algorithm.


Blockchain, NFT (non-fungible token), KNN (K-Nearest Neighbours).

Published in: 3rd Asia Pacific International Conference on Industrial Engineering and Operations Management, Johor Bahru, Malaysia

Publisher: IEOM Society International
Date of Conference: September 13-15, 2022

ISBN: 978-1-7923-9162-0
ISSN/E-ISSN: 2169-8767