Ryan Prananda Hikmahanto
Sistem Informasi, UIN Syarif Hidayatullah Jakarta

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SELECTION OF SCRYPT ALGORITHM ASICS USING THE WEIGHTED AGGREGATED SUM PRODUCT ASSESSMENT (WASPAS) METHOD Maulana Asykari Muhammad; Ryan Prananda Hikmahanto; Muhammad Zidan Fatonie
JATI (Jurnal Mahasiswa Teknik Informatika) Vol. 10 No. 2 (2026): JATI Vol. 10 No. 2
Publisher : Institut Teknologi Nasional Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36040/jati.v10i2.17552

Abstract

The cryptocurrency mining industry faces significant challenges due to the increasing difficulty of the Scrypt algorithm, which necessitates highly efficient hardware to maintain profitability. Selecting the optimal Application-Specific Integrated Circuit (ASIC) is a complex Multi-Criteria Decision Making (MCDM) problem because it involves conflicting variables such as hashrate, power consumption, energy efficiency, price, and daily profit. This study aims to assess this complexity and provide a systematic decision-making framework by determining the most optimal ASIC device for the Scrypt algorithm. We implemented the Weighted Aggregated Sum Product Assessment (WASPAS) method, combining the Weighted Sum Model (WSM) and Weighted Product Model (WPM) to evaluate and rank ten recent ASIC models to enhance ranking accuracy and stability. The results indicated the Bitmain Antminer L9 (16 GH/s) as the optimal device with a preference value of 0.742. Conversely, the device with the highest raw hashrate, the VolcMiner D1 Hydro, only ranked 7th. This proves that superior computational speed does not guarantee operational viability when energy efficiency and investment costs are factored in. These findings can serve as a reference for a systematic decision-making framework for miners to prioritize sustainable hardware, and provide technical insights for manufacturers regarding market preferences for energy-efficient designs.