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All Journal Jurnal Ilmu Komputer dan Sistem Komputer Terapan (JIKSTRA) Buletin Utama Teknik
Siregar, Muhammad Ramulia
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Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Electrical & Electronics Engineering Industrial & Manufacturing Engineering

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Journal : Jurnal Ilmu Komputer dan Sistem Komputer Terapan (JIKSTRA)

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Analisis Penerapan Waspas dan Topsis pada Sistem Pendukung Keputusan dalam Memilih Aset Digital NFT Guna Siregar, Muhammad Ramulia; Lubis, Imran; Budiman, Arief; Budi, Budi
Jurnal Ilmu Komputer dan Sistem Komputer Terapan (JIKSTRA) Vol. 6 No. 2 (2024): Edisi Oktober
Publisher : Universitas Harapan Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35447/jikstra.v6i2.1039

Abstract

The development of blockchain technology, especially Non-Fungible Tokens (NFT), has created challenges for investors in determining the right investment value. This study aims to develop a decision support system using the Weighted Aggregated Sum Product Assessment (WASPAS) method and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to assess NFT as an investment alternative. The research process involves several stages, including problem identification, problem analysis, literature study, data collection, and data analysis. The criteria used in assessing NFT include price, owner/origin, format, rarity, and industry, each with a set weight. After collecting data on various NFTs, a decision matrix is ​​constructed and normalized to reflect the performance of each alternative. The WASPAS and TOPSIS methods are used to assign preference values ​​to each NFT alternative based on their proximity to the positive and negative ideal solutions. The analysis results show that NFT named "Video Clip" (A3) has the highest value with a preference of 0.671, followed by "Song" (A5) with a value of 0.445, and "Book" (A2) with a value of 0.465. Meanwhile, "Selvie Photo" (A4) and "Photo" (A1) have the lowest preferences of 0.196 and 0.189, respectively. This study contributes to NFT investment decision making, by providing a systematic and data-driven approach that can reduce risk and maximize potential profits for investors. The combination of WASPAS and TOPSIS methods offers a comprehensive framework for NFT valuation, so that it can be adopted by investors and NFT platform developers in evaluating the value of digital assets more effectively.
Co-Authors Arief Budiman Budi Budi Imran Lubis