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Robbi Rahim
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sana@mediadigitalpublikasi.com
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JL. Kenari 18 No. 421 Desa/Kelurahan. Kenangan, Kec. Percut Sei Tuan, Kab. Deli Serdang, Kab. Deli Serdang, Provinsi Sumatera Utara, 20226, Indonesia
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INDONESIA
Journal of Blockchain, Nfts and Metaverse Technology
Published by CV. Media Digital Publikasi Indonesia
ISSN : -     EISSN : 30309832     DOI : 10.58905/sana
Core Subject : Science, Engineering,
Computer Science & IT Decision Sciences, Operations Research & Management Engineering Library & Information Science
This Journal scope includes, but is not limited to, the following areas: Blockchain architecture, protocols, and security Non-fungible tokens (NFTs) and their applications in the creative industries, gaming, and more Metaverse technology and virtual worlds, including the development and governance of decentralized autonomous organizations Tokenomics and economics of blockchain and NFTs Legal and regulatory frameworks for blockchain and NFTs The intersection of blockchain, NFTs, and metaverse technology with other fields such as finance, gaming, and the arts The journal welcomes contributions from a wide range of disciplines, including computer science, economics, law, and the arts. The journal is committed to fostering an open and inclusive scholarly community and to promoting diversity, equity, and inclusiveness in all its endeavors. With its focus on blockchain, NFTs, and metaverse technology, SaNa: Journal of Blockchain, NFTs and Metaverse Technology aims to provide a valuable resource for researchers, practitioners, policymakers, and industry leaders seeking to understand and advance the capabilities of these cutting-edge technologies.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 15 Documents
 1   2 
Non-Fungible Tokens: A Literature Review Hokianto, Hugo Fostin
SaNa: Journal of Blockchain, NFTs and Metaverse Technology Vol. 1 No. 1 (2023): August 2023
Publisher : CV. Media Digital Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58905/sana.v1i1.32

Abstract

Non-Fungible Tokens (NFTs) was a popular crypto asset in the year 2021-2022, where viral news involving a NFT with huge price being sold causes a big interest to NFTs and OpenSea, one of the biggest NFT market place, and creating supply and demand for buying and selling NFTs, especially people who are only aware of cryptocurrency becoming the one who buys cryptocurrency and crypto assets. Although NFTs has since lost its initial exposure, the literatures of NFTs remains scarce, and the research involving NFTs has since been lower. This research is aimed to reviews literatures involving NFTs, using literature review method with „NFTs“ or „Non-Fungible Tokens“ as keywords to search for relevant literatures and research articles. The result of the research gave a definitive definition of NFTs compiled from many authors, the method people use to create NFTs and ways to invest NFTs safely, opportunities and risks in investing NFTs and the technological aspect, and what the future has for NFTs, investing and technological wise.
Analysis of Distributed File System Replication Using the NDLC Method with Hyper-V Virtual Simulation Machine Sumirat, Ucu; Setiawan, Antonius; Wilyanti, Sinka; Al-Hakim, Rosyid
SaNa: Journal of Blockchain, NFTs and Metaverse Technology Vol. 1 No. 1 (2023): August 2023
Publisher : CV. Media Digital Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58905/sana.v1i1.59

Abstract

The need to access file sharing easily on an organization's computer network was increased. Users didn't have to worry about the number of file server addresses that can be accessed and are made with only one access address to use file sharing. The availability of data on the network to file storage availability in an organization was also essential. Data would be permanently lost, following a reason including hardware failure, or even accidentally deleted. It was important to ensure that there was a copy of the data. Achieving good data availability requires a system strategy built in the organization's data center. This research used Distributed File System Replication (DFSR) based on active directory domain services with Windows Server. The research method used NDLC (Network Diagram Life Cycle) method. This research was conducted through analysis with the Hyper-V virtual simulation machine. The results of the research with this simulation are that the Distributed File System (DFS) makes it easy for users to access file shares on several file server nodes using only one URL address. DFSR makes it easy for users to clone files automatically on multiple nodes file servers at other locations. DFSR, with its Share and Publish features, provide good data availability. If one of the file server nodes experiences an interruption, the file server nodes at another location would be taken over to provide the data. This system makes it easy for administrators to manage file servers
Cryptocurrency Exchange Selection Decision Support System Using Preference Selection Index Prasetyo, Dwi; Ariati, Nining; Lubis, Harmoko; Akbar, Aswin
SaNa: Journal of Blockchain, NFTs and Metaverse Technology Vol. 1 No. 1 (2023): August 2023
Publisher : CV. Media Digital Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58905/sana.v1i1.148

Abstract

Cryptocurrency trading is a very popular business of buying and selling digital money today. Many investors trade cryptocurrency assets through cryptocurrency exchange platforms in the hope of getting a large profit difference. However, the cryptocurrency trading business is not always favourable for investors as choosing the wrong cryptocurrency exchange can result in huge losses from the trades made. Based on these problems, it is necessary to have a decision support system for selecting the most relevant cryptocurrency exchange to be used as a cryptocurrency trading platform that can increase the chances of investors making profits. The decision support system method used in this research is Preference Selection Index (PSI). The results of the selection of cryptocurrency exchanges using the Preference Selection Index (PSI) method in this study recommend Indodax as the most relevant cryptocurrency exchange used by investors to gain profits in running a cryptocurrency trading business because it gets the highest value (0.893662729) compared to 4 other alternatives.
Decision Support System for Selecting the Best Cryptocurrency Mining Machine Using the Multifactor Evaluation Process Method Mashuri, Chamdan; Sitompul, Bernad J. D.; Vernanda, Dwi; Marbun, Nasib
SaNa: Journal of Blockchain, NFTs and Metaverse Technology Vol. 1 No. 1 (2023): August 2023
Publisher : CV. Media Digital Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58905/sana.v1i1.152

Abstract

Cryptocurrency mining is a process carried out using a specialised computer network in order to obtain new crypto assets. The cryptocurrency mining business in today's digital era is increasingly in demand by netizens. Many netizens run cryptocurrency mining businesses to generate new cryptocurrency assets that can be traded on the cryptocurrency market to earn huge profits. In doing cryptocurrency mining itself, it is necessary to be careful in choosing the cryptocurrency mining machine used to get the maximum profit. In this study, researchers proposed the Multifactor Evaluation Process as a decision support system method used to simplify the process of selecting the best cryptocurrency mining machine. The results of this study show that the best cryptocurrency mining machine that is most recommended to use is Cheetah Miner F5I (0.2120), followed by the alternatives iBeLink DSM7T Miner (0.2072), Bitfury RD4 (0.2016), Aladdin T1 16T (0.2016), and Obelisk SC1 Dual (0.1800).
Selection of Digital Investment Instruments Applying the Multi-Objective Optimization by Ratio Analysis Method Patria, Lintang; Marbun, Nasib; Sitompul, Bernad J. D.; Simangunsong, Pandi Barita Nauli
SaNa: Journal of Blockchain, NFTs and Metaverse Technology Vol. 1 No. 1 (2023): August 2023
Publisher : CV. Media Digital Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58905/sana.v1i1.187

Abstract

Choosing a digital investment instrument to make digital investments is not easy because behind the expected profits are also accompanied by balanced risks. Therefore, not a few novice investors are confused to determine the choice of digital investment instruments that are most appropriate for use in the long term. In this study the authors applied the decision support system method (Multi-Objective Optimization by Ratio Analysis) to facilitate the decision-making process in choosing digital investments for novice investors. The results of this study indicate that Alternative A4 (Trading) with a value of 0.17097 has the highest value compared to other alternatives, so Alternative A4 (Trading) is the most recommended digital investment instrument for use by novice investors.
The Implementation of E-Commerce for Frozen Food Products in Providing Recommendations Using Item-Based Collaborative Filtering Method Simanungkalit, Racquel Terranova; Triayudi, Agung; Benrahman
SaNa: Journal of Blockchain, NFTs and Metaverse Technology Vol. 2 No. 2 (2024): August 2024
Publisher : CV. Media Digital Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58905/sana.v2i2.262

Abstract

The development of information technology, especially the internet, has significantly impacted facilitating human access to information, including the trend of society opting for frozen food as a fast food option. Meanwhile, the phenomenon of social media depicts the tendency of society to choose convenient and fast food. On the other hand, the rapid development of sales and product promotion systems through the internet is taking place, utilizing web-based technology. Recent studies also indicate that the development of web-based sales information systems for frozen food can enhance efficiency and service quality. Collaborative filtering methods in recommendation systems are also becoming increasingly popular in helping users obtain better recommendations. All of this indicates that information technology has had a positive impact on making purchasing and information management more efficient and convenient for society
Analysis of K-NN Algorithm and Linear Regression to Predict House Prices in Jabodetabek Nadia Putri Ariyanti; Agung Triayudi; Ratih Titi Komala Sari
SaNa: Journal of Blockchain, NFTs and Metaverse Technology Vol. 2 No. 1 (2024): February 2024
Publisher : CV. Media Digital Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58905/sana.v2i1.265

Abstract

Jabodetabek is now the region with the highest average level of citizen satisfaction, so many people migrate to this region in the hope of getting better living conditions, this will make people who want to buy a house question whether the house they want to buy is good value or not. The purpose of this study is to evaluate the effectiveness of multiple linear regression and K-Nearest Neighbors (KNN) algorithm on a dataset of house prices in Jabodetabek. Better results are obtained by using the Multiple Linear Regression model which has lower Mean Absolute Error (MAE) and Mean Squared Error (MSE) values and a fairly good R-squared of around 48.72%. However, the very high MAE and MSE values of the KNN model indicate inaccuracy and significant prediction variance. Although KNN has a relatively high R-squared value, more research is needed to see if the model can adequately explain data fluctuations. Based on the performance evaluation, multiple linear regression is ultimately a better choice
Sentiment Analysis on Twitter Using Naïve Bayes and Logistic Regression for the 2024 Presidential Election Alisya Mutia Mantika; Agung Triayudi; Rima Tamara Aldisa
SaNa: Journal of Blockchain, NFTs and Metaverse Technology Vol. 2 No. 1 (2024): February 2024
Publisher : CV. Media Digital Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58905/sana.v2i1.267

Abstract

In accordance with the notion of democracy which is the basis of the state of Indonesia, general elections will be held in 2024. In the implementation of the General Election there is a campaign to lead the public vote to choose the best candidate according to public opinion. Twitter social media is one of the media to voice opinions as well as share information to become one of the indirect campaigning platforms. Social media also does not escape negative issues, community rumors, and even the digital footprint of presidential candidates which can be a very important consideration in campaigning. This research aims to see the public's response to the 2024 presidential candidates. This research is conducted based on public opinion on presidential candidates, then public opinion data taken from Twitter social media will go through a pre-processing process to clean the data before the data is classified into Naive Bayes and Linear Regression modeling. The two classification models are then sought for the highest performance accuracy value and confusion matrix with 80:20 splitting data. The results showed that the Naive Bayes classification model had a higher accuracy value than the Logistic Regression classification model, which was 63% for Anies Baswedan candidate, 77% for Ganjar Pranowo candidate, and 44% for Prabowo Subianto. The highest accuracy value was obtained by the sentiment data of 2024 presidential candidate Ganjar Pranowo, which was 77%.
Analysis of the Effect of User Satisfaction on the Quality of the Shopee Application with the End User Computing Satisfaction Method (Survey on Followers of the Shopee Indonesia Instagram Account) Baldhan Difa; Agung Triayudi; Endah Tri Esti Handayani
SaNa: Journal of Blockchain, NFTs and Metaverse Technology Vol. 2 No. 2 (2024): August 2024
Publisher : CV. Media Digital Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58905/sana.v2i2.269

Abstract

Shopee is one of the e-commerce platforms in Indonesia that supports the marketplace business model. Shopee faces a big challenge to compete with a large number of other e-commerce because it is one of the marketplaces that enliven the mobile segment. To win the competition, marketplace organizers must be able to meet consumer needs to win the competition because the rapid and diverse growth of e-commerce results in increasingly fierce competition. A service can be said to be successful in providing satisfaction if it can meet the needs of its users, and user satisfaction itself can be interpreted as an important thing for every service provider. User satisfaction with services can be used to identify the good and bad sides of services that can be implemented so that user needs can be met. In this study, the End User Computer Satisfaction (EUCS) method is used, the EUCS method has 5 variables that can be used in the analysis process, namely the Content, Accuracy, Format, Ease of Use, and Timeliness variables. The research was conducted by distributing questionnaires to @shopee_id Instagram followers, from distributing questionnaires, 385 data were taken as samples to measure Shopee marketplace user satisfaction. The results of the presentation of Shopee marketplace user satisfaction on all variables are stated to have a very satisfactory data interpretation because the presentation value is above 81%
Implementation of Face Recognition for Lecturer Attendance Using Deep Learning CNN Algorithm Fajhar Muhammad; Agung Triayudi; Eri Mardiani
SaNa: Journal of Blockchain, NFTs and Metaverse Technology Vol. 2 No. 1 (2024): February 2024
Publisher : CV. Media Digital Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58905/sana.v2i1.270

Abstract

Using the Convolutional Neural Network (CNN) algorithm, this research aims to create a better lecturer attendance application that improves the attendance system and creates peace of mind when lecturers arrive at national universities. The author analyses the results of applying deep learning algorithms to an experimental face recognition system that uses convolutional neural networks. The purpose of this study is to show that deep learning algorithms can improve the accuracy and efficiency of recording presence. In addition, the goal of this research is to create a timekeeping application using face recognition technology that is expected to have a high level of accuracy. In addition, this research includes a modification of the CNN model. This modification resulted in an epoch value of 75 for training of 100% and test of 95%. Analysis of results, drawing conclusions, and suggestions for additional development are the final stages of this research. Evaluation of the integrated system is done by collecting actual attendance data and comparing it with the attendance records created by the system. This validation will help explain the performance of the system and find problems or vulnerabilities that may need to be fixed.

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