Arda, Muhammad Adhli
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IMPLEMENTATION OF HASHLIPS ART ENGINE TO EARN IMAGE VARIATIONS ON NON-FUNGIBLE TOKEN (NFT) Arda, Muhammad Adhli; Setiaji, Bayu
Jurnal Pilar Nusa Mandiri Vol 18 No 2 (2022): Pilar Nusa Mandiri : Journal of Computing and Information System Publishing Peri
Publisher : LPPM Universitas Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/pilar.v18i2.3898

Abstract

Non-Fungible Token (NFT) is a blockchain-based token that securely maps copyright ownership to digital assets, these digital assets exist on the blockchain network which have identification codes and metadata that are unique and different from each other (one-of-the-kind). . It can also be interpreted as a digital asset that represents a variety of assets that are considered unique. NFTs can be traded for digital assets (images, music, videos, virtual creations) where ownership is recorded in a smart contract on the blockchain. One of the difficulties faced is that it takes a very long time for NFT creators to create a large number of works of art in a short time. To make it easier for creators to create NFT images, Daniel Eugene Botha, or better known as Hashlips, created a Hashlips Art Engine algorithm that can be used to create many different NFT images based on the layers provided using the canvas API and node.js. The hashlips algorithm also generates metadata as an important role in the mechanism for searching and exchanging NFT data and measuring the percentage of rarity in the resulting image. In addition, this study also shows the time required to create NFT images.