Analisis Penerapan Waspas dan Topsis pada Sistem Pendukung Keputusan dalam Memilih Aset Digital NFT Guna

  • Muhammad Ramulia Siregar Prodi Teknik Informatika, Fakultas Teknik dan Komputer, Universitas Harapan Medan, Medan, Indonesia
  • Imran Lubis Prodi Teknik Informatika, Fakultas Teknik dan Komputer, Universitas Harapan Medan, Medan, Indonesia
  • Arief Budiman Prodi Teknik Informatika, Fakultas Teknik dan Komputer, Universitas Harapan Medan, Medan, Indonesia
  • Budi Budi Prodi Teknik Informatika, Fakultas Teknik dan Komputer, Universitas Harapan Medan, Medan, Indonesia
DOI: https://doi.org/10.35447/jikstra.v6i2.1039
Keywords: Non fungible Token, waspas method, , topsis method, video clip

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.

 

 

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Author Biography

Budi Budi, Prodi Teknik Informatika, Fakultas Teknik dan Komputer, Universitas Harapan Medan, Medan, Indonesia

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.

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Published
2024-10-31
Issue
Vol 6 No 2 (2024): Edisi Oktober
Section
Articles
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